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Auterion builds a cutting-edge operating system for autonomous robotic systems that empower a diverse range of platforms to perform surveillance, reconnaissance, inspection, mapping and logistics tasks. Our industry-leading software drives the adoption of robotic fleets and is recognized by the U.S. government as the future standard for its drone programs. We are looking for a Senior Embedded Performance Engineer who is passionate about getting the most out of embedded systems — from low-level Linux tuning and hardware integration to high-performance video and data pipelines. This role is ideal for someone who enjoys working close to hardware, moving across the stack, and solving the kinds of problems where milliseconds, bandwidth, startup time, and system efficiency matter. You will work across the AuterionOS ecosystem on topics such as: Embedded Linux performance and system tuning Low-latency video streaming and media pipelines C/C++, Python, and Bash-based platform development Hardware integration, system profiling, and end-to-end optimization Collaboration with experienced and driven engineers across Auterion Responsibilities Work within the Apps & Simulation team and collaborate with other development teams to build high-performance products for autonomous systems. Design, optimize, and maintain performance-critical components within AuterionOS, Auterion's custom embedded Linux distribution. Improve end-to-end system behavior across compute, networking, video, and hardware interfaces, with a strong focus on latency, throughput, reliability, and resource efficiency. Analyze and optimize demanding workloads such as real-time telemetry, video streaming, media processing, and communication between distributed system components. Investigate system bottlenecks across the full stack, from kernel and OS behavior to application-level code and tooling. Collaborate with engineering and product teams to understand both internal and customer use cases, and translate them into robust technical solutions. Propose and implement new platform capabilities with a strong emphasis on measurable performance gains in real-world deployments. Participate in daily stand-ups, release planning, and prioritization discussions. Qualifications and Skills B.Sc. or M.Sc. in Computer Science, Software Engineering, or a related field. 5+ years of professional experience writing object-oriented C++ and/or Python. Deep experience with embedded Linux systems, including cross-compilation, debugging, profiling, and performance tuning. Strong hands-on background in diagnosing and optimizing real-world system behavior, including CPU, memory, I/O, networking, boot time, and application latency. Experience building or optimizing low-latency video or data-streaming pipelines, ideally on embedded platforms. Excellent understanding of software systems that span embedded devices, higher-level applications, and fully integrated products. Strong software engineering fundamentals, including system design, implementation, debugging, and testing. Experience with video codecs, GStreamer, RTP/RTSP, or hardware-accelerated media pipelines. Solid experience with Debian/Ubuntu-based systems, Bash scripting, and systemd. Experience with Docker and docker-compose in complex development and deployment environments, as well as qemu. Strong debugging and performance analysis skills at both system and application level, combined with a proactive and self-directed working style. Proficient in ROS2/DDS-style middleware and experienced with networking across multiple OSI layers, including REST APIs and performance-sensitive communication paths. Experience with system integration and interfacing sensors or peripherals, especially via USB and Ethernet. Experience working in an agile engineering environment with stand-ups, sprint planning, and shared ownership across teams. Bonus: Experience with build systems such as CMake, including improving build performance in large-scale software projects. Benefits Flexible working hours Stock Options Generous holiday allowance Company pension plan Car parking Enhanced maternity & paternity leave Mental health and wellbeing support Learning and development opportunities About Auterion We are building the leading software platform for AI-powered autonomous systems for enterprise and government customers. Our team is supporting the most important missions and solving the most challenging problems. At Auterion, we bring together the sharpest minds who love to solve the hardest problems. Join a vibrant team built on innovation, openness, and excellence, where you'll be empowered to develop ideas, collaborate across all levels, and make an impact that matters. Find more English Speaking Jobs in Switzerland on Arbeitnow

About Mirakl: Founded in 2012, Mirakl has been at the forefront of marketplace innovation, empowering every business to compete in the platform economy. Today, Mirakl's operating system combines an enterprise marketplace solution (Mirakl Platform) that enables retailers and B2B organizations to launch, scale, and operate marketplaces and dropship, AI-powered multichannel selling (Mirakl Connect), retail media (Mirakl Ads) and an agentic commerce infrastructure (Mirakl Nexus). With dual headquarters in Boston and Paris, Mirakl helps a global ecosystem of 450+ marketplaces (B2C and B2B) and a network of over 100k third-party marketplace sellers. Brands like Macy's, Decathlon, Carrefour, Asos, and Airbus Helicopters use Mirakl to grow their businesses in new and remarkable ways. For more information: www.mirakl.com . Mirakl in Numbers: 🗓️ Founded in 2012 | Member of French Tech Next40 👥 750+ employees in 9 offices worldwide: Paris, Barcelona, Bordeaux, Boston, London, Munich, New York, Sydney, Tokyo 🇫🇷 350+ Mirakl Tech teams members mainly based in France ⚙️ 5 Saas Solutions Our Values: Working at Mirakl means accelerating your career alongside ambitious, passionate, and supportive colleagues. We're proud of the diversity of backgrounds, perspectives, and experiences that make our teams unique. Our 5 values guide how we collaborate: 💡 Work Hard Together: Teamwork and collaboration are the foundation of our success 🏆 Get Things Done: We prioritize action and efficiency for impactful results 🚀 Go Above & Beyond: We tackle challenges proactively and always aim for excellence 🎓 Succeed Through Expertise: Knowledge sharing and continuous learning are core to our culture 🤝 Satisfy & Empower Clients: We're committed to our clients' success About the job Design, build, and scale production-grade AI systems that power the next generation of intelligent commerce. You will work at the intersection of Software Engineering, Machine Learning, and Generative AI to build AI-native products, agentic systems, and platform capabilities used by Mirakl customers and internal teams. This is a freelance position based in Paris or Bordeaux, with 1 day of remote work per week. Why Now, Why Mirakl Generative AI and AI Agents are fundamentally reshaping commerce software and the way our teams work on a day to day basis. At Mirakl, AI is becoming a core part of our product strategy. From Catalog Transformer and content generation to AI Agents and Agentic Commerce, we are building the next generation of commerce software. And we have the same ambition for our teams around AI products and adoption. We are looking for a Senior AI Engineer to transform the way our internal teams work, and to have a significant impact on the agentic side of our Saas products. You won't be joining a company that's thinking about AI. You'll be joining one that's already building it. What You'll Do 1. Design & Build AI Systems Design, build, and deploy production-grade AI systems for both Mirakl internal operations. Develop solutions leveraging: LLMs, RAG, AI Agents, Multimodal AI and Evaluation frameworks. Architect complex agentic workflows including tools, memory, retrieval, planning, and guardrails. Rapidly prototype new capabilities and evolve them into scalable, reliable AI production systems. 2. Integrate Across the Stack Connect AI systems to internal platforms, business applications, and data sources across the company. Enable AI agents to interact with systems such as CRM, data platform, Drive, Jira, support tools, and internal knowledge bases. Design robust orchestration layers between models, APIs, tools, retrieval systems, and business workflows. Ensure reliability, observability, scalability, and maintainability across the entire AI stack. 3. Iterate for Impact Partner with end users, business teams, Product Managers, and Engineers to identify high-value opportunities for AI. Run pilots and experiments, gather qualitative and quantitative feedback, and measure business impact. Analyze usage patterns, failure modes, costs, latency, and performance metrics. Continuously improve accuracy, reliability, adoption, and user experience through data-driven iteration. 4. Ensure Quality, Security & Reliability Implement evaluation frameworks, guardrails, validation layers, and monitoring systems. Design AI systems that are secure, explainable, and production-ready. Ensure compliance with data security, governance, and access control requirements. Document architectures, capabilities, limitations, KPIs, and operational best practices. 5. Drive Adoption & Enablement Build a scalable ecosystem of AI systems and agents that empower both internal teams and customers. Support teams in adopting AI-powered workflows and integrating AI into their daily operations. Contribute to AI engineering standards, reusable frameworks, and best practices across the company. Act as a champion for AI-driven ways of working and help shape Mirakl's transition toward Agentic Commerce. Our stack and tools Languages: Python and SQL AI Stack: OpenAI, Anthropic, Gemini, Mistral and Open-source models Agentic & Retrieval: LangGraph, LangChain, LlamaIndex, MCP and Vector Databases Infrastructure: AWS or GCP, Docker and Kubernetes What Makes You Successful Strong engineering mindset: able to design reliable and scalable systems Strong AI expertise: able to translate the latest AI capabilities into production products Strong product mindset: able to balance technical excellence with business impact Focus on measurable outcomes, not technical complexity Success Metrics Product adoption and business impact Performance and reliability of AI systems Quality of AI outputs and evaluation metrics You'll Love This Job If you have 5+ years of experience in Software Engineering, ML Engineering, Applied AI, or related fields Strong Python and software engineering fundamentals Hands-on experience building production AI systems using LLMs, RAG, and AI Agents Experience designing multi-step agentic workflows and retrieval systems Experience evaluating AI systems and improving model performance Experience deploying and operating production services in cloud environments Strong communication skills in English Curiosity, pragmatism, and passion for building AI products Feel free to add a link to your GitHub in your CV so we can understand what you have worked on! Want to join us? Here is our process A 30-40 min phone conversation with one of our Tech recruiters. This will be an opportunity to discuss your background, expectations, and discover what Mirakl can offer you in return. An initial 1h30 technical discussion with a member of the Data Science team and Engineering Team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects. 2 x 45-minute "STAR" interviews with future Mirakl colleagues to discuss our values and company culture. We welcome collaborators with their diverse perspectives and experiences to power us forward. These often far exceed conventional job requirements and help us create a culture of continuous learning. If you're ready to join a global leader powering digital transformation for 450+ of the world's most innovative retailers and B2B organizations. As part of our recruitment process, Mirakl processes your personal data to review and manage your application and, where appropriate, to consider your profile for future opportunities. You can exercise your data protection rights at any time, and as further detailed in our policies. For more information about how we process your personal data and your rights, please consult our Recruitment Privacy Notice, here in English and here in French. We may use Artificial Intelligence (AI) solutions to help streamline our hiring process, including screening applications, analyzing resumes, and assessing responses. While AI helps us work efficiently, all final hiring decisions are made by humans. For more information, visit our AI Guidelines for Candidates and Interviews . Find more English Speaking Jobs in France on Arbeitnow

About Mirakl: Founded in 2012, Mirakl has been at the forefront of marketplace innovation, empowering every business to compete in the platform economy. Today, Mirakl's operating system combines an enterprise marketplace solution (Mirakl Platform) that enables retailers and B2B organizations to launch, scale, and operate marketplaces and dropship, AI-powered multichannel selling (Mirakl Connect), retail media (Mirakl Ads) and an agentic commerce infrastructure (Mirakl Nexus). With dual headquarters in Boston and Paris, Mirakl helps a global ecosystem of 450+ marketplaces (B2C and B2B) and a network of over 100k third-party marketplace sellers. Brands like Macy's, Decathlon, Carrefour, Asos, and Airbus Helicopters use Mirakl to grow their businesses in new and remarkable ways. For more information: www.mirakl.com . Mirakl in Numbers: 🗓️ Founded in 2012 | Member of French Tech Next40 👥 750+ employees in 9 offices worldwide: Paris, Barcelona, Bordeaux, Boston, London, Munich, New York, Sydney, Tokyo 🇫🇷 350+ Mirakl Tech teams members mainly based in France ⚙️ 5 Saas Solutions Our Values: Working at Mirakl means accelerating your career alongside ambitious, passionate, and supportive colleagues. We're proud of the diversity of backgrounds, perspectives, and experiences that make our teams unique. Our 5 values guide how we collaborate: 💡 Work Hard Together: Teamwork and collaboration are the foundation of our success 🏆 Get Things Done: We prioritize action and efficiency for impactful results 🚀 Go Above & Beyond: We tackle challenges proactively and always aim for excellence 🎓 Succeed Through Expertise: Knowledge sharing and continuous learning are core to our culture 🤝 Satisfy & Empower Clients: We're committed to our clients' success About the job Design, build, and scale production-grade AI systems that power the next generation of intelligent commerce. You will work at the intersection of Software Engineering, Machine Learning, and Generative AI to build AI-native products, agentic systems, and platform capabilities used by Mirakl customers and internal teams. This is a freelance position based in Paris or Bordeaux, with 1 day of remote work per week. Why Now, Why Mirakl Generative AI and AI Agents are fundamentally reshaping commerce software and the way our teams work on a day to day basis. At Mirakl, AI is becoming a core part of our product strategy. From Catalog Transformer and content generation to AI Agents and Agentic Commerce, we are building the next generation of commerce software. And we have the same ambition for our teams around AI products and adoption. We are looking for a Senior AI Engineer to transform the way our internal teams work, and to have a significant impact on the agentic side of our Saas products. You won't be joining a company that's thinking about AI. You'll be joining one that's already building it. What You'll Do 1. Design & Build AI Systems Design, build, and deploy production-grade AI systems for both Mirakl internal operations. Develop solutions leveraging: LLMs, RAG, AI Agents, Multimodal AI and Evaluation frameworks. Architect complex agentic workflows including tools, memory, retrieval, planning, and guardrails. Rapidly prototype new capabilities and evolve them into scalable, reliable AI production systems. 2. Integrate Across the Stack Connect AI systems to internal platforms, business applications, and data sources across the company. Enable AI agents to interact with systems such as CRM, data platform, Drive, Jira, support tools, and internal knowledge bases. Design robust orchestration layers between models, APIs, tools, retrieval systems, and business workflows. Ensure reliability, observability, scalability, and maintainability across the entire AI stack. 3. Iterate for Impact Partner with end users, business teams, Product Managers, and Engineers to identify high-value opportunities for AI. Run pilots and experiments, gather qualitative and quantitative feedback, and measure business impact. Analyze usage patterns, failure modes, costs, latency, and performance metrics. Continuously improve accuracy, reliability, adoption, and user experience through data-driven iteration. 4. Ensure Quality, Security & Reliability Implement evaluation frameworks, guardrails, validation layers, and monitoring systems. Design AI systems that are secure, explainable, and production-ready. Ensure compliance with data security, governance, and access control requirements. Document architectures, capabilities, limitations, KPIs, and operational best practices. 5. Drive Adoption & Enablement Build a scalable ecosystem of AI systems and agents that empower both internal teams and customers. Support teams in adopting AI-powered workflows and integrating AI into their daily operations. Contribute to AI engineering standards, reusable frameworks, and best practices across the company. Act as a champion for AI-driven ways of working and help shape Mirakl's transition toward Agentic Commerce. Our stack and tools Languages: Python and SQL AI Stack: OpenAI, Anthropic, Gemini, Mistral and Open-source models Agentic & Retrieval: LangGraph, LangChain, LlamaIndex, MCP and Vector Databases Infrastructure: AWS or GCP, Docker and Kubernetes What Makes You Successful Strong engineering mindset: able to design reliable and scalable systems Strong AI expertise: able to translate the latest AI capabilities into production products Strong product mindset: able to balance technical excellence with business impact Focus on measurable outcomes, not technical complexity Success Metrics Product adoption and business impact Performance and reliability of AI systems Quality of AI outputs and evaluation metrics You'll Love This Job If you have 5+ years of experience in Software Engineering, ML Engineering, Applied AI, or related fields Strong Python and software engineering fundamentals Hands-on experience building production AI systems using LLMs, RAG, and AI Agents Experience designing multi-step agentic workflows and retrieval systems Experience evaluating AI systems and improving model performance Experience deploying and operating production services in cloud environments Strong communication skills in English Curiosity, pragmatism, and passion for building AI products Feel free to add a link to your GitHub in your CV so we can understand what you have worked on! Want to join us? Here is our process A 30-40 min phone conversation with one of our Tech recruiters. This will be an opportunity to discuss your background, expectations, and discover what Mirakl can offer you in return. An initial 1h30 technical discussion with a member of the Data Science team and Engineering Team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects. 2 x 45-minute "STAR" interviews with future Mirakl colleagues to discuss our values and company culture. We welcome collaborators with their diverse perspectives and experiences to power us forward. These often far exceed conventional job requirements and help us create a culture of continuous learning. If you're ready to join a global leader powering digital transformation for 450+ of the world's most innovative retailers and B2B organizations. As part of our recruitment process, Mirakl processes your personal data to review and manage your application and, where appropriate, to consider your profile for future opportunities. You can exercise your data protection rights at any time, and as further detailed in our policies. For more information about how we process your personal data and your rights, please consult our Recruitment Privacy Notice, here in English and here in French. We may use Artificial Intelligence (AI) solutions to help streamline our hiring process, including screening applications, analyzing resumes, and assessing responses. While AI helps us work efficiently, all final hiring decisions are made by humans. For more information, visit our AI Guidelines for Candidates and Interviews . Find Jobs in France on Arbeitnow

Location: Bristol, UK (hybrid, three days a week in the office) Level: Staff Engineer (TL2) Team: Security Engineering, within the Cyber Security squad Salary: £105,600 – £132,000 + discretionary bonus Contract: Permanent Reporting to: Senior Software Engineering Manager Please note: This role requires an existing right to work in the UK . We can't offer visa sponsorship, but we review sponsorship role by role, so keep an eye on our careers site for future opportunities. About Kaluza Kaluza is the Energy Intelligence Platform, turning energy complexity into seamless coordination. We help energy companies overcome today's challenges while accelerating the shift to a clean, electrified future. Our platform orchestrates millions of real-time decisions across homes, devices, markets and grids. By combining predictive algorithms with human-centred design, Kaluza makes clean energy dependable, affordable and adaptive to everyday life. With teams across Europe, Asia and Australia, and a joint venture with Mitsubishi Corporation in Japan, we power leading companies including OVO, AGL and ENGIE, as well as innovators like Volvo and Volkswagen. What you'll do You'll join the Security Engineering team, working alongside our cyber security leadership, architecture team and technical leaders across engineering. Our mission is to equip teams to build and innovate while upholding security best practice and protecting client data in the highly regulated energy sector. Integrate security tooling and use AI to prevent, detect and respond to emerging threats Work with senior technical leadership to shape our technical strategy and solutions architecture, so security, risk and compliance feed into technical decisions Help product teams deliver secure systems quickly by building a strong security culture through mentoring, design reviews and training Give product and engineering teams practical guidance on identifying, prioritising and mitigating systemic risks and vulnerabilities Lead the evolution of our security best practice across application development and the wider SDLC, supporting teams with expert advice and automation Influence technical and non-technical stakeholders across Kaluza and client teams Mentor and coach security and software engineers to balance risk with speed and quality Build relationships with third-party security vendors and industry bodies to keep us at the forefront of emerging practices, tooling and standards What you'll bring Ideally, you'll have: Extensive experience mentoring engineers and collaborating closely (e.g. pairing, swarming) Deep understanding of software security flaws and web application security best practice (OWASP Top 10, CWE/SANS Top 25) Extensive knowledge of CI/CD and DevOps principles, and their security considerations Experience applying AI in your own work and helping others build it safely into how they develop Scripting skills and first-hand experience of software development at scale Working knowledge of Okta or equivalent, to enable workforce identity and enforce access management policies Awareness of AWS and/or GCP security best practice, and some experience with infrastructure as code (e.g. Terraform) Experience applying architectural and software design patterns in a complex environment You'll also be: A pragmatic, risk-based decision-maker who weighs the technical and commercial consequences of your choices Skilled at influencing upwards and outwards, with great communication skills Able to set a clear vision for large-scale technical direction and align multiple teams behind it Keen to drive compliance and NFR improvements that balance information security and commercial goals Committed to a culture of learning and improvement, and willing to challenge engineering leadership to support it Skills (SFIA): We use the SFIA framework to assess and develop our security engineers. Levels run from 1 to 7. Essential: Level 6: Systems design Level 5: Information security , specialist advice , systems development lifecycle , solution architecture , emerging technology monitoring Level 4: Information assurance , information and data compliance Desirable: Identity and access management (Level 5), software development (Level 6), learning delivery (Level 3), and information assurance stepping up to Level 5 Our values Five values guide how we work at Kaluza: Play to win: Collective pride in decarbonising energy at scale. Solve the real problem: Cutting through complexity to focus on real-world outcomes. Build trust every day: Consistency, transparency and doing what we say. Own the outcome: Full accountability, wins and setbacks, without ego. Go further together: Collaboration, respect and different perspectives. Our perks Time off and family: 26 days' holiday [plus/including bank holidays], plus 26 weeks' full pay for new parents with no qualifying service period Health and security: Private medical insurance with virtual GP, life assurance, pension scheme, free mortgage advice and eye tests Pay and flexibility: Discretionary bonus, a Flex Fund of 5% [of salary] to spend on the benefits you want most, retail discounts through Perks at Work Growth and setup: Personal learning budget, home office budget Climate: Furthr, our climate action app Come as you are We want to meet people from all walks of life. The more inclusive we are, the better our work will be, and we recognise talent on merit and potential. If you're excited about the role but don't tick every box, we'd still love to hear from you. If you need any adjustments during the process, just let us know. Find out more on our careers page and LinkedIn , or read our Applicant Data Protection Policy . Find more English Speaking Jobs in United Kingdom on Arbeitnow

About the role Radiant exists to redefine how AI infrastructure is built and operated at scale. We are creating a vertically integrated AI platform that brings together physical infrastructure, control planes, and cloud-native software to deliver abundance, control, and sovereignty in a world constrained by traditional hyperscaler models. Our vision is to enable organisations to build, train, and deploy AI at national and global scale without surrendering control over performance, cost, or locality. This requires engineering systems that operate across software, hardware, and physical environments, and that remain reliable as scale and complexity increase. We are scaling our engineering organisation now. Most of our engineering manager seats are open. You join, shape how the teams work, and grow with them. As an Engineering Manager, you lead a team building and operating core parts of Radiant's cloud platform. You combine people leadership, technical judgement, delivery ownership and cross-functional collaboration. You work closely with product, infrastructure, SRE, security and other engineering teams. This is a hands-on leadership role. It focuses on building strong teams, delivering reliable platform capabilities, and creating an environment where engineers do their best work. The streams We run engineering as ten streams in three groups. Each stream is a full team of about nine people: principal, senior and mid-level software engineers, an SDET, a DevOps engineer and a platform engineer. Each stream has its own engineering manager. Infrastructure: Compute, Network, Storage, Cluster Platform: Cloud, Infra, Observability, Security AI: Training, Inference You do not apply for a single stream. We hire strong managers first. Then we agree your stream with you, based on your strengths and interests. Your first stream is a starting point, not a fixed track. Moves between streams are normal here. Key responsibilities You lead one stream end to end: people, delivery and production. Lead, coach and develop a team of about nine engineers across platform, infrastructure and distributed systems. Own team execution across planning, prioritisation, delivery, quality and operational readiness. Partner with product to turn priorities into clear technical plans and achievable milestones. Provide technical leadership on architecture, reliability, scalability and engineering trade-offs. Set strong engineering practices for design, testing, observability, documentation and incident learning. Improve team effectiveness through clear ownership, healthy processes and strong cross-team collaboration. Hire, onboard and retain high-performing engineers. Hiring is a large part of the first year. Expect around two hours a day on it. Support career development through regular feedback, coaching and progression planning. Manage technical risk, dependencies and delivery challenges across complex platform initiatives. Bring AI-assisted engineering into daily work, within our guardrails. Build a culture of ownership, pragmatism, operational excellence and continuous improvement. Attitude comes first Curiosity: you learn new domains fast. GPUs, networks and storage excite you rather than worry you. Candour: you say what you think, with care. You welcome challenge to your own ideas. Builder mindset: much here is not built yet. You enjoy creating the process, not just running it. Pace with standards: you move fast and keep quality high. Generosity: you make the people around you better. You give credit and share what you know. Your profile Experience leading engineering teams building cloud platforms, infrastructure, developer tooling or distributed systems. A strong technical background. You engage credibly in architecture and design discussions. A good understanding of: Cloud infrastructure: compute, storage, networking, Kubernetes, containers Platform engineering: APIs, automation, IAM, observability, reliability Distributed systems: scaling, consistency, failure handling Engineering operations: incident response, capacity, performance, production ownership Proven experience in people management, hiring, coaching and performance development. Strong delivery and prioritisation skills across competing priorities. Comfort working closely with product and other engineering leaders in an ambiguous, fast-moving environment. The ability to balance technical quality, delivery speed, reliability and team sustainability. Experience with GPU, HPC or AI infrastructure is a bonus. Nobody has depth in every area above. Tell us which you know and which you want to learn. What you bring People leadership: you build strong teams and help engineers grow. Technical judgement: you challenge designs and guide trade-offs without owning every implementation detail. Execution: you create clarity and drive complex work to completion. Systems thinking: you understand how platform components and teams fit together. Operational mindset: you care about reliability, maintainability and production quality. Ownership: you take responsibility for both team health and engineering outcomes. Find more English Speaking Jobs in United Kingdom on Arbeitnow

Job title: Machine Learning Engineer – Lumen Enterprise Models (SWE-focused LLMs) Location: London; full in-office working as default Start date: ASAP Reports to: CEO Compensation: Salary and Equity options available for discussion Application deadline: 08/11/26 at 23:59 UK time ___________________________________________________________________________ Help train the software engineers of the future Cosine is building autonomous software-engineering systems for organisations where reliability, security and control matter most. Our Lumen Enterprise models are designed to work across real codebases. They need to understand unfamiliar architectures, make changes across multiple files, use tools, run tests and produce software that engineers can maintain and trust. We're looking for a Machine Learning Engineer to help train and improve these models. You'll work across the full training stack, including pre-training, supervised fine-tuning and reinforcement learning. This is a truly unique role that will provide exposure across all areas of the model training lifecycle. WE're looking for someone who is just as happy to profile the training loop, identifying performance bottlenecks and memory leaks, as implementing new RL algorithms. This is a hands-on role for someone who enjoys working close to the model and cares about the quality of the software it produces. ___________________________________________________________________________ The role You'll work closely with research, infrastructure and product to answer questions such as: What should Lumen learn next? Which data and environments will teach it most effectively? How should we reward correct, maintainable and useful software? How do we train models to work across large repositories and long contexts? How do we know when a model is genuinely better for engineers? The models you train will write code, use development tools, run tests and receive feedback from real software-engineering environments. Your work will directly influence how Lumen reasons about code, navigates unfamiliar systems and improves through experience. ___________________________________________________________________________ Why this role matters The best coding models are not simply the ones that generate plausible code. They need to understand context, respect existing architecture, use tools effectively, test their work and recover when their first attempt fails. They need to produce changes that work in the real world, not just on a benchmark. That behaviour has to be trained. You'll work directly on the data, environments, rewards and evaluations that shape Lumen's capabilities. Your work will influence the models used by engineers and enterprise teams working on complex and security-sensitive software systems. This is an opportunity to work on frontier model training while staying close to a concrete, high-value outcome: building AI that can genuinely do software engineering. ___________________________________________________________________________ What you'll do Work across the full training lifecycle, running pre-training, supervised fine-tuning and reinforcement-learning experiments. Optimize training methods at scale on frontier models. Diagnose and fix performance bottlenecks and communication overhead in distributed training environments. Train models on long-context, multi-file and repository-level tasks. Develop RL and RLVR loops using signals from execution, tests, linters, static analysis and other engineering feedback, turning fresh ideas into scalable, reproducible code. Investigate model failure modes such as poor planning, brittle fixes, reward hacking and regressions. Collaborate with infrastructure, platform and data teams. ___________________________________________________________________________ What we're looking for You may come from machine learning research, applied ML, model training or a closely related engineering background. You should have: Strong experience training deep-learning models in a production or research environment. Deep practical experience with PyTorch or a comparable framework. Experience with distributed training and multi-GPU systems (FSDP, Deepspeed, …) Strong software-engineering fundamentals and a high bar for correctness and maintainability. Clear communication and the ability to explain technical trade-offs. Experience with large language models is important. You should have worked meaningfully on at least one of, pre-training, SFT, preference optimisation, RLHF or RLVR. We care more about depth of understanding and evidence of strong technical judgement than about having used every tool listed. Even if you don't tick every box, please consider applying! A bonus if you have Experience with mixture-of-experts (MoE) architectures. Experience with CUDA. Familiarity with vLLM, SGLang or other high-performance inference systems. Experience running jobs on SLURM, Kubernetes or managed GPU platforms. Experience with code-model benchmarks such as SWE-bench, HumanEval or internal repository-level evaluations. Contributions to open-source model-training, RL or evaluation tools. ___________________________________________________________________________ Why join Cosine Direct impact: Your work directly shapes the next generations of Lumen Enterprise SWE models that engineers use every day. Real scale: You'll work with large, modern open-source models, long context lengths, and multi-node training runs. Full-stack ML engineering: From custom PyTorch code and distributed systems to data curation, RL design and MLOps. Research + pragmatism: You'll stay close to the latest literature in SFT, and code LLMs, but you'll be judged by shipped improvements, not just ideas. If this sounds like a fit, this is a role where you can meaningfully push the frontier of open-source–based software engineering models. ___________________________________________________________________________ Cosine is an equal opportunity employer. We value diverse backgrounds, perspectives, and ways of thinking, and we're committed to creating an inclusive and respectful workplace. We encourage applications from anyone who meets the role requirements, even if you don't meet every single qualification. If you need reasonable adjustments at any stage of the hiring process, we're happy to discuss them. ___________________________________________________________________________ Compensation, Benefits & Ways of Working We're an in-office team, five days a week, by design. We believe the work we're doing benefits from being together, collaborating closely, and building shared context. What you can expect: Competitive salary , benchmarked to the market Equity / share options , so you share in the upside you help create 30 days' holiday + bank holidays Work hard in the office, collaborate closely, and switch off properly Dog-friendly office — bring your dog to work Weekly team breakfast & lunch Monthly socials Pension High-quality equipment to do your best work We care about focus, sustainability, and doing great work — not performative overwork. We value people who show up, contribute thoughtfully, collaborate well with their colleagues, and then go home. This role won't suit everyone. But if you're looking for a fast-moving environment, close collaboration, and a team that takes both the work and work-life balance seriously, it's a great place to be. ___________________________________________________________________________ Agency & Data Protection Notice To comply with UK GDPR and our internal data-protection and equal-opportunity obligations, we only accept candidate applications and agency submissions via our Applicant Tracking System (ATS). This ensures appropriate privacy notices, lawful processing, auditability, and consistent retention controls. Any CVs or candidate details received outside the ATS (including via email, Slack, or direct message) will be treated as unsolicited, will not be considered as part of the recruitment process, and will not give rise to any fee or payment obligation. Find Jobs in United Kingdom on Arbeitnow

Job title: Applied ML Technical Lead, Defence Location: London; full in-office working as default Start date: ASAP Reports to: CEO Compensation: Salary and Equity options available for discussion Clearance: Must be eligible to hold UK Security Vetting Clearance SC or above (no prior clearance required) Application Deadline: 08/11/26 at 23:59 UK Time ___________________________________________________________________________ Help put frontier AI to work in Defence Cosine is a UK AI lab building models, applications and training infrastructure for mission-critical organisations. We build coding agents that work across real software systems, specialised Lumen models, AI-native security products and the infrastructure needed to deploy advanced AI in demanding environments. Our customers include some of the world's largest enterprises, including organisations operating behind strict security, regulatory and technical constraints. We're also training Lumen Sovereign, the first frontier large language model trained in the UK, with the support of the UK Government. We're now looking for an Applied ML Technical Lead to help develop and deploy advanced AI capabilities for organisations operating in UK Defence and national security. This is a hands-on technical leadership role. You will work across machine learning development, deployment and customer-facing technical delivery. You may spend part of your time training and evaluating models on complex sensor data, and part of your time working with Defence stakeholders to understand operational needs, shape priorities and guide delivery. You will not be expected to act as a traditional project manager. Instead, you will own the technical direction and day-to-day progress of applied ML work, coordinating the people and decisions needed to turn promising research into useful operational capability. ___________________________________________________________________________ What you'll do Build ML capabilities for real Defence problems Design, build, train and evaluate machine learning models for challenging applied Defence and national security use cases. Work on problems involving complex sensor data, signal processing, pattern recognition, classification and multimodal intelligence. Develop and improve model architectures, training pipelines, evaluation frameworks and inference systems. Work with real-world and synthetic datasets to improve model accuracy, robustness and generalisation. Translate research prototypes into reliable, deployable capabilities that operate within demanding technical and security constraints. Work closely with Cosine's ML research and engineering teams while taking direct ownership of technical outcomes. Lead technical delivery from prototype to deployment Own the technical direction and day-to-day progress of applied ML projects. Turn operational objectives into concrete technical goals, experiments, milestones and success measures. Coordinate work across ML researchers, software engineers, infrastructure teams and external stakeholders. Identify technical dependencies, delivery risks and blockers, and help drive them to resolution. Establish clear evaluation criteria and demonstrate progress through measurable improvements and working capabilities. Balance hands-on engineering with the planning and coordination needed to keep complex technical work moving. Work directly with Defence customers Engage with technical and operational stakeholders across the UK Defence and national security ecosystem. Understand operational challenges and identify where machine learning can make a meaningful difference. Translate customer requirements and constraints into technical objectives, datasets, experiments and delivery plans. Present technical progress, demonstrate working capabilities and communicate results clearly to technical and non-technical audiences. Build trusted relationships with Defence stakeholders and act as a credible technical counterpart. Help customers understand the practical considerations of integrating and deploying ML systems in their existing environments. Turn research into operational capability Help deploy ML models into real-world environments, including secure, on-premise and resource-constrained systems. Work on model optimisation, inference performance, integration and reliability. Develop robust approaches to evaluation, validation and continuous model improvement. Understand data availability, access requirements, security restrictions and deployment constraints. Establish feedback loops between operational users and Cosine's engineering teams. Ensure that what we build is not only technically impressive, but genuinely useful to the people relying on it. ___________________________________________________________________________ What we're looking for You'll probably have a background in applied machine learning, ML engineering, research engineering or a similarly technical role, along with experience taking ownership of complex technical work. You should be comfortable: Writing production-quality Python and working with modern ML frameworks such as PyTorch. Building, training, fine-tuning and evaluating machine learning models. Working with complex datasets, designing experiments and interpreting model performance. Understanding the trade-offs between model performance, compute requirements, latency and deployment constraints. Working with engineering infrastructure, including Git, containers, Linux and GPU compute. Taking technical ownership of projects with multiple stakeholders, uncertain requirements and evolving priorities. Communicating technical concepts clearly to researchers, engineers, senior stakeholders and operational users. Moving between model development, customer discussions and delivery planning without losing technical depth. Making sound technical judgements, prioritising effectively and finding practical solutions when the path forward is unclear. You don't need to have worked in Defence before. You do need to be excited by the opportunity to apply advanced ML to difficult, consequential real-world problems. Nice to have Existing UK security clearance, such as SC or DV, or previous experience working in secure Defence environments. Experience with signal processing, time-series data, sensor fusion, representation learning or machine learning applied to complex real-world datasets. Experience with foundation models, multimodal learning or advanced model training and post-training techniques. Experience deploying ML models to edge devices or constrained compute environments. Familiarity with UK Defence procurement, technical assurance or the national security landscape. Experience leading technical workstreams or working as a technical lead on customer-facing ML projects. ___________________________________________________________________________ What success looks like In your first three months, we would expect you to: Become the technical lead for a major applied Defence ML programme, with responsibility for its day-to-day technical progress. Build strong working relationships with Cosine's ML researchers, engineers and key Defence customer stakeholders. Develop a clear understanding of the existing models, datasets, technical architecture and operational objectives. Establish a focused delivery plan with clear priorities, milestones, ownership and success measures. Make meaningful hands-on contributions to model development, evaluation or deployment. Identify and begin addressing the most important technical and operational blockers. Demonstrate tangible progress to customer stakeholders and build confidence in Cosine's ability to deliver. Longer term, you'll help take advanced ML capabilities from promising prototypes into operational use, while shaping how Cosine builds and delivers applied AI for Defence and other mission-critical organisations. ___________________________________________________________________________ Why this role matters Some of the most important applications of AI won't be found in consumer products. They'll be in environments where information is incomplete, systems are complex, security matters and the consequences of getting things wrong are significant. Cosine is working to bring frontier machine learning into those environments. Doing that requires more than good models. It requires people who can understand an operational problem, build something that works, make good technical decisions, coordinate the work needed to deliver it and stay close to the customer until it creates real value. You'll have unusual proximity to cutting-edge ML research, senior Defence stakeholders and the operational challenges that will shape the next generation of AI capabilities. This role will suit someone who is technically strong enough to build, organised enough to lead technical delivery and curious enough to engage directly with the people using the technology. If you enjoy being close to the research, close to customers and personally accountable for turning ambitious technology into something real, come and work with us. Come help make frontier AI useful where it matters most. ___________________________________________________________________________ Cosine is an equal opportunity employer. We value diverse backgrounds, perspectives, and ways of thinking, and we're committed to creating an inclusive and respectful workplace. We encourage applications from anyone who meets the role requirements, even if you don't meet every single qualification. If you need reasonable adjustments at any stage of the hiring process, we're happy to discuss them. ___________________________________________________________________________ Compensation, Benefits & Ways of Working We're an in-office team, five days a week, by design. We believe the work we're doing benefits from being together, collaborating closely, and building shared context. What you can expect: Competitive salary , benchmarked to the market Equity / share options , so you share in the upside you help create 30 days' holiday + bank holidays Work hard in the office, collaborate closely, and switch off properly Dog-friendly office — bring your dog to work Weekly team breakfast & lunch Monthly socials Pension High-quality equipment to do your best work We care about focus, sustainability, and doing great work — not performative overwork. We value people who show up, contribute thoughtfully, collaborate well with their colleagues, and then go home. This role won't suit everyone. But if you're looking for a fast-moving environment, close collaboration, and a team that takes both the work and work-life balance seriously, it's a great place to be. ___________________________________________________________________________ Agency & Data Protection Notice To comply with UK GDPR and our internal data-protection and equal-opportunity obligations, we only accept candidate applications and agency submissions via our Applicant Tracking System (ATS). This ensures appropriate privacy notices, lawful processing, audibility, and consistent retention controls. Any CVs or candidate details received outside the ATS (including via email, Slack, or direct message) will be treated as unsolicited, will not be considered as part of the recruitment process, and will not give rise to any fee or payment obligation. Find Jobs in United Kingdom on Arbeitnow

About Fractile Fractile was founded in 2022 on the bet that, eventually, the world's most capable AI systems would be limited in their impact by the time taken to produce useful outputs. We bet everything on the logical conclusion: that the only way to truly unlock this latent value, to make speed viable at scale, was to radically re-invent the hardware that we run our frontier AI models on. Ever since, we have been building chips and systems that tackle this problem: how to efficiently generate output at thousands of tokens per second, while handling the complexity and capacity challenges of operating large models at very long contexts. The workloads that push to the limits of the current frontier are already transformational; it is the technical and economic limits on inference speed that are constraining progress. The defining work of the 21st century will be marked by the engine of inference delivering immense and diffuse chains of intellectual inquiry, in drug discovery, in software engineering, in materials discovery, in any field where progress is driven by deep reasoning and intelligence to resolve complex problems. About Fractile Fractile was founded in 2022 on the bet that, eventually, the world's most capable AI systems would be limited in their impact by the time taken to produce useful outputs. We bet everything on the logical conclusion: that the only way to truly unlock this latent value, to make speed viable at scale, was to radically re-invent the hardware that we run our frontier AI models on. Ever since, we have been building chips and systems that tackle this problem: how to efficiently generate output at thousands of tokens per second, while handling the complexity and capacity challenges of operating large models at very long contexts. The workloads that push to the limits of the current frontier are already transformational; it is the technical and economic limits on inference speed that are constraining progress. The defining work of the 21st century will be marked by the engine of inference delivering immense and diffuse chains of intellectual inquiry, in drug discovery, in software engineering, in materials discovery, in any field where progress is driven by deep reasoning and intelligence to resolve complex problems. About the role Based in the UK you will be a key member of the Manufacturing Operations team where you will drive the development of our business management systems as well as our product, supplier, software and customer quality initiatives. You will be comfortable with assessing processes and technologies to identify quality gaps and provide robust but pragmatic solutions to drive all aspects of the business in achieving the highest levels of quality and resilience. Key responsibilities Define and deliver the company quality strategy, policy and objectives, aligned to the product roadmap and growth plan. Build, lead and develop a quality team covering supplier, product, reliability, software and systems quality. Define and report quality performance to the executive team. Establish appropriate document control, change control, CAPA, internal audit, training and records processes that scale with a fast-growing fabless company. Work with PMO to embed quality gates into the new product introduction (NPI) and product lifecycle process, from concept through end of life. Own quality across the supply chain: wafer foundry, assembly and packaging, wafer and final test, PCB/PCBA and system-level contract manufacturers. Lead supplier selection, qualification, audits and ongoing performance management, including scorecards and quarterly business reviews. Work with engineering leaders to define software quality standards across drivers, firmware, compilers, SDKs and runtime. Establish release criteria, test coverage expectations, defect management and regression processes, aligned with CI/CD practice. Bring in secure development and software supply chain practice, including SBOMs and vulnerability management. Support responsible AI and AI management practice where customers ask for it, including awareness of ISO/IEC 42001. Be the senior point of contact for customer quality, audits and escalations. Lead customer RMA and complaint handling, root cause analysis and 8D responses to agreed timelines. Ensure product compliance with RoHS, REACH, WEEE, conflict minerals reporting, UKCA and CE marking, and relevant safety and EMC standards. Essential experience and skills Significant experience in quality roles in semiconductors or electronics hardware, including creating and leading a quality function or team. Direct experience managing quality through outsourced manufacturing: foundries, OSATs, test houses and/or contract manufacturers. Deep knowledge of ISO 9001 and hands-on experience building or running a certified QMS. Working knowledge of semiconductor qualification and reliability (JEDEC), failure analysis and Awareness of data centre RAS assessments and HPC system qualification and certification. Fluency in core quality tools: 8D, FMEA, control plans, SPC, MSA and root cause analysis. Experience handling customer quality escalations with large, demanding customers. Degree in electrical or electronic engineering, materials science, physics or a related discipline. Clear, confident communicator who can influence engineers, suppliers and executives, and hold partners to account. Willing to travel internationally, including to Asia and US, for supplier audits and customer quality reviews. Desirable Experience in a fabless company, particularly one bringing an initial product to volume. Background in high-performance compute, data centre, networking or AI hardware. Exposure to software quality, release management or secure development practice. Lead auditor certification (ISO 9001), Six Sigma Black Belt, or chartered status (for example CQI or IET). Experience working with suppliers in Taiwan, South Korea or US. The impact you will have You will help Fractile to makes sure every one of our suppliers builds to our standard, and that our customers receive AI hardware and software they can trust in production whilst shaping the quality culture across engineering, operations and commercial teams. What We Offer Competitive salary: A competitive salary reflective of your experience and the specialist nature of the role. Equity & Ownership: meaningful equity so everyone shares in the value creation. Benefits: Private Medical, Dental and Vision, Contributory Pension, 25 Days holiday plus bank holidays and Life/Critical Illness Insurance. Diverse & fun office: we believe the hardest problems get solved by the broadest range of minds. We are committed to Equal Employment Opportunity through attracting and retaining a diverse team and building an inclusive environment. Fractile is seeking to increase the clock speed of global progress, one chip at a time. We've recently raised $220M from investors including Founders Fund and Accel and our most important work lies ahead. Join us! Export controls Our work involves technologies subject to UK, US and other international export control regulations. Certain roles may require additional eligibility checks to ensure compliance with applicable law. We'll be transparent about this throughout the hiring process. What We Offer Competitive salary: A competitive salary reflective of your experience and the specialist nature of the role. Equity & Ownership: meaningful equity so everyone shares in the value creation Benefits: Private Medical, Dental and Vision, Contributory Pension, 25 Days holiday plus bank holidays and Life/Critical Illness Insurance. Diverse & fun office: we believe the hardest problems get solved by the broadest range of minds. We are committed to Equal Employment Opportunity through attracting and retaining a diverse team and building an inclusive environment. Fractile is seeking to increase the clock speed of global progress, one chip at a time. We've recently raised $220M from investors including Founders Fund and Accel and our most important work lies ahead. Join us! Export controls Our work involves technologies subject to UK, US and other international export control regulations. Certain roles may require additional eligibility checks to ensure compliance with applicable law. We'll be transparent about this throughout the hiring process. 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At Statista , we're all about facts and data, for we are the world's leading business data platform. By providing reliable and easy-to-use data as well as various data analytics products and services, we empower people worldwide to make fact-based decisions. Founded in Hamburg in 2007, we have quickly grown into a global company with offices in major cities such as London, New York, Berlin and Tokyo. And we still have a lot of plans. Our constant growth does not only prove our success, but also keeps creating new development and career opportunities for our employees. We value and celebrate our diverse culture. You are welcome here for who you are, no matter where you come from, what you look like, or whether you prefer bar graphs to pie charts. Your story matters – keep writing it as part of our team. Are you ready to join us? About the Role As Data Engineer on our Healthcare Platform, you will own the foundational data ingestion, entity-resolution, and platform infrastructure end-to-end. You will design and operate scalable batch/streaming data pipelines, harden platform orchestration, and ensure system reliability, security, and cost efficiency. A central challenge of this role is building and operationalizing our unified healthcare data ontology —a consistent semantic model covering hospitals, departments, specialties, metrics, and classification standards. Working closely with Analytics Engineers, Data Scientists, and Methodology experts, you will turn heterogeneous, multi-country hospital data into a coherent, highly queryable data asset. Key Responsibilities Pipeline Infrastructure & Orchestration: Build, optimize, and operate reliable ELT pipelines (using Python, SQL, and Prefect/Airflow) to ingest data from heterogeneous international sources, APIs, databases, and lakehouse storage (S3, Apache Iceberg). Healthcare Ontology & Entity Resolution: Drive the implementation of entity resolution and master data management (MDM) for international hospital entities, mapping raw source data to canonical structures and maintaining standardized vocabularies (e.g., ICD/OPS, specialty taxonomies). Data Contracts & Schema Governance: Establish strict data contracts (Pydantic, dbt contracts) and schema management, ensuring dataset reproducibility, data lineage tracking, and automated validation across all platform pipelines. Platform Efficiency & Cloud Infrastructure: Optimize data storage, query execution, and compute costs across AWS and Snowflake, keeping data assets performant, secure, and cost-effective. Automation & CI/CD: Implement automated testing and deployment workflows for data pipelines using GitHub Actions and Infrastructure as Code (Terraform). Cross-Functional Data Enablement: Partner directly with Analytics Engineers, Data Scientists, and domain experts to deliver documented, research-grade, and production-ready datasets. Qualifications Core Requirements (Must-Haves) Data Ingestion & Pipeline Orchestration: Advanced Python and analytical SQL for complex data ingestion across diverse file formats, REST APIs, databases, and cloud lakes (S3/Iceberg). Hands-on experience with modern orchestrators (Prefect, Airflow, or Dagster). Entity Resolution & Data Governance: Practical experience with entity resolution/record linkage frameworks (e.g., Splink, dedupe, recordlinkage) and schema management/data contracts (Pydantic, dbt contracts, or JSON Schema). Cloud Platform & Warehouse Infrastructure: Deep hands-on experience in an AWS production environment (S3, ECS/EC2) combined with cloud data warehouses (Snowflake). Automated CI/CD & Workflow Automation: Proven track record of automating data pipeline deployments, integration tests, and validation workflows via GitHub Actions. Nice-to-Haves (What Will Make You Stand Out) Knowledge Graphs & Healthcare Terminologies: Exposure to ontology/semantic frameworks (RDF/OWL, SKOS, Neo4j, LinkML) or international medical classifications/vocabularies (SNOMED CT, ICD/OPS, FHIR). Metadata & Lineage Tooling: Experience operating metadata registries and lineage catalogs (e.g., OpenMetadata, DataHub, dbt docs). Infrastructure as Code (IaC): Proficiency in using Terraform to declaratively manage cloud resources and environments. Your Profile Degree: Bachelor's or Master's in Computer Science, Data Science, Software Engineering, or a related quantitative field. Experience: 3+ years in data engineering building production pipelines and data platforms; including a sustained period within one organization seeing a core platform or product through build → launch → iteration. Domain Knowledge: Healthcare domain experience is a plus (basic understanding of healthcare KPIs, quality metrics, or benchmarking concepts; familiarity with hospital structures and medical classification systems like ICD/OPS is especially valuable). Mindset: Strong analytical and systems mindset, with a proven ability to transform messy, heterogeneous international data into a clean, well-governed, and highly structured data asset. Languages: Fluent in English, German is a plus. Working Style: Highly structured, curious, detail-oriented, and motivated to collaborate closely with analytics engineers, data scientists, and methodology experts in an international environment. What we offer In addition to our great team, culture, and our shared goal of empowering people with data, there are many other things that make Statista a great place to work! Join us and benefit from: Work from abroad up to 30 calendar days a year Hybrid work and flex-time International team and social events Subsidized urban mobility and access to fitness and wellness options Free access to Langdock and all its amazing functionalities Career & training opportunities Attractive locations and modern offices Mental health support with OpenUp Some of the benefits listed here apply only to the German entity and to Junior-level roles or above. Find Jobs in Germany on Arbeitnow

About Graphcore Graphcore is one of the world's leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world's most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore's teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed systems. The Team An exciting opportunity to join a new team within the Software Operations group. The Build Engineering team is a new function within Software Infrastructure, which focuses on the overall process of building and integration of the Machine Learn ing S oftware S tack. You will work closely with the QA and development teams to get an understanding of how our ML SW stack is built, helping to ensure good build practices, and proving that the stack works together and is reproducible in secure, sandboxed environments. Responsibilities and Duties Developing our internal tooling for building, testing and integrating together the ML Software Stack Developing tools and technical processes for Software Releases Providing guidance to developers on best build practices and dependency management Communicating regularly with developers, tech leads, and software architects about aspects of the ML Software Stack Working closely with QA and the ML Software Stack to resolve any integration issues Contributing fixes towards the ML Software Stack Essential: Knowledge of Python/C++ (or similar language) Understanding of Build Processes and Frameworks Experience working in Linux environments Good communication skills Desirable: Experience with Remote Caching and Execution (e.g. Bazel) Experience with Build Tools (e.g. CMake) Experience with Testing Frameworks (e.g. PyTest, GoogleTest) Experience with Integration Tools (e.g. Buildstream) Experience working within the Software Development Lifecycle (SDLC) Experience with building and using containers (e.g. Docker, Podman) An understanding of Software Architecture patterns Benefits In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we're committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments. Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications Find more English Speaking Jobs in United Kingdom on Arbeitnow

About Graphcore Graphcore is one of the world's leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world's most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore's teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed systems. The Team An exciting opportunity to join a new team within the Software Operations group. The Build Engineering team is a new function within Software Infrastructure, which focuses on the overall process of building and integration of the Machine Learn ing S oftware S tack. You will work closely with the QA and development teams to get an understanding of how our ML SW stack is built, helping to ensure good build practices, and proving that the stack works together and is reproducible in secure, sandboxed environments. Responsibilities and Duties Developing our internal tooling for building, testing and integrating together the ML Software Stack Developing tools and technical processes for Software Releases Providing guidance to developers on best build practices and dependency management Communicating regularly with developers, tech leads, and software architects about aspects of the ML Software Stack Working closely with QA and the ML Software Stack to resolve any integration issues Contributing fixes towards the ML Software Stack Essential: Knowledge of Python/C++ (or similar language) Understanding of Build Processes and Frameworks Experience working in Linux environments Good communication skills Desirable: Experience with Remote Caching and Execution (e.g. Bazel) Experience with Build Tools (e.g. CMake) Experience with Testing Frameworks (e.g. PyTest, GoogleTest) Experience with Integration Tools (e.g. Buildstream) Experience working within the Software Development Lifecycle (SDLC) Experience with building and using containers (e.g. Docker, Podman) An understanding of Software Architecture patterns Benefits In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we're committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments. Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications Find more English Speaking Jobs in United Kingdom on Arbeitnow

About Graphcore Graphcore is one of the world's leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world's most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore's teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed systems. The Team An exciting opportunity to join a new team within the Software Operations group. The Build Engineering team is a new function within Software Infrastructure, which focuses on the overall process of building and integration of the Machine Learn ing S oftware S tack. You will work closely with the QA and development teams to get an understanding of how our ML SW stack is built, helping to ensure good build practices, and proving that the stack works together and is reproducible in secure, sandboxed environments. Responsibilities and Duties Developing our internal tooling for building, testing and integrating together the ML Software Stack Developing tools and technical processes for Software Releases Providing guidance to developers on best build practices and dependency management Communicating regularly with developers, tech leads, and software architects about aspects of the ML Software Stack Working closely with QA and the ML Software Stack to resolve any integration issues Contributing fixes towards the ML Software Stack Essential: Knowledge of Python/C++ (or similar language) Understanding of Build Processes and Frameworks Experience working in Linux environments Good communication skills Desirable: Experience with Remote Caching and Execution (e.g. Bazel) Experience with Build Tools (e.g. CMake) Experience with Testing Frameworks (e.g. PyTest, GoogleTest) Experience with Integration Tools (e.g. Buildstream) Experience working within the Software Development Lifecycle (SDLC) Experience with building and using containers (e.g. Docker, Podman) An understanding of Software Architecture patterns Benefits In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we're committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments. Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications Find Jobs in United Kingdom on Arbeitnow