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Adaptyv is building an automated lab that lets AI agents run biology experiments. We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world. We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today. Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development. We're growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation. About the Role We build our lab automation ourselves. Instead of buying turnkey systems and running them through a vendor's GUI, we reverse-engineer instruments, control them with open-source Python tooling like PyLabRobot and PyHamilton , and build the software and hardware to turn a pile of instruments into work cells that run biology around the clock. We're looking for a Lab Automation Engineer to help design, build, and run these systems. This is a broad role: on any given week you might be writing a driver for a new instrument, getting a liquid handler and a robot arm to hand off cleanly, or debugging why an overnight run stalled. We care far more about range, ability, and drive than years on any one platform. What You'll Do Control lab instruments — liquid handlers, robot arms, plate readers, incubators, analytical devices — programmatically in Python, ideally with PyLabRobot / PyHamilton, rather than locking workflows into proprietary software. Build and integrate work cells: get multiple instruments working together as one orchestrated unit that runs unattended. Bring new instruments online by reverse-engineering their control protocols and building drivers that expose them to the rest of the stack. Write the software glue — drivers, integrations, small services — that connects hardware to our platform (mostly Python, with some TypeScript). Partner with biologists to turn new assays into reliable automated workflows, then keep them running: diagnosing and fixing the mechanical, electrical, and software failures that come with 24/7 production. Push throughput and reliability up continuously — better error recovery, smarter scheduling, sturdier hardware. What We're Looking For Maker and hacker attitude. You like taking systems apart, figuring out how they work, and building the thing that makes them work better. You'd rather script an instrument than click through it. Strong software engineering skills. You write real Python and can structure code others can maintain — drivers, integrations, services — not just throwaway scripts. You'll pick up TypeScript where needed. Lab automation experience. Hands-on with PyHamilton, PyLabRobot, Opentrons, or similar tooling is a strong plus. Direct experience automating instruments and workflows matters more than the specific platform. Self-starter and independent. You see what needs building and build it. You don't wait for a spec, and you don't need a vendor training course to get going. AI-native builder. It's 2026 — you build with coding agents like Claude Code as a default, and you have sharp judgment about what they produce. Hardware comfort is a plus. Electronics, microcontrollers, 3D printing, CAD, or fabrication experience all help, but they're not required if your software and automation skills are strong. Debugging instinct. When something fails mid-run, you reason across software, firmware, electronics, and mechanics to find the cause and fix it. Biology background not required — but you should be excited that the robots run real experiments. Details Location: Lausanne, Switzerland (on-site — you're building physical systems) Type: Full time Start date: ASAP Application deadline We are reviewing applicants on a rolling basis. Find Jobs in Switzerland on Arbeitnow

Adaptyv is building an automated lab that lets AI agents run biology experiments. We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world. We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today. Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development. We're growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation. About the Role You'll work in our biology & production team running protein expression, DNA assembly, and characterization workflows. We run thousands of constructs per week across cell-free and cell-based expression systems, high-throughput DNA synthesis and assembly, and binding/stability characterization (BLI, SPR, enzymatic assays). What You'll Do Run protein expression workflows: cell-free (PURE, lysate-based), E. coli, and potentially mammalian systems. Execute DNA synthesis and assembly protocols at high throughput: PCR, Golden Gate, Gibson. Run binding and characterization assays: BLI, SPR, thermostability, enzyme activity, developability assays. Troubleshoot when proteins don't express, misfold, or aggregate. Prepare reagents, manage samples, and track experiments in LabOS. Analyze experimental data: expression gels, chromatograms, binding curves. Work with the automation team to adapt bench protocols for robotic workflows. What We're Looking For BSc / MSc in molecular biology, biochemistry, or a relevant field. Hands-on bench time matters more than the degree. Practical molecular biology skills: PCR, cloning, gel electrophoresis, DNA purification. You've done these yourself, not just read about them. Protein expression experience. You've expressed recombinant proteins in at least one system and understand the basics. Experience with DNA assembly methods (Golden Gate, Gibson, restriction cloning). High-throughput experience is a plus. Familiarity with biophysical and analytical characterization techniques. We use BLI, SPR, plate reader assays, nanoDSF, HPLC-SEC, and CE-SDS. You don't need all of them, but you should have hands-on experience with at least a few. Comfortable scripting in Python or similar. You don't need to be a software engineer, but you should be able to write a script to parse data, generate plate maps, or automate a repetitive analysis. Organized and precise. Hundreds of constructs per week means you track everything and follow protocols exactly. Strong work ethic. Experiments don't always finish at 6pm. Comfortable in a fast-paced environment where priorities shift and you figure things out yourself. Details Location: Lausanne, Switzerland (on-site) Type: Full time Start date: ASAP Application deadline We are reviewing applicants on a rolling basis. Find Jobs in Switzerland on Arbeitnow

Adaptyv is building an automated lab that lets AI agents run biology experiments. We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world. We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today. Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development. We're growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation. About the role You'll build backend systems that make our lab programmable. You'll architect data pipelines that process large-scale protein characterization data, build APIs that integrate laboratory instruments and robotics into our software stack, and work closely with scientists and automation engineers to translate complex molecular biology workflows into reliable, scalable software. This is not SaaS slop, you're making physical machines do precise biology with minimal human intervention. What we're looking for Strong experience designing and building production backend systems. We use Python and TypeScript on the backend with Postgres, but what matters is that you can architect systems that are reliable and maintainable. Experience building data pipelines and processing infrastructure. You'll be handling large volumes of heterogeneous data from physical instruments such as binding kinetics data, enzyme activity measurements, chromatography readings, and turning them into clean, structured datasets. Comfortable with API design and systems integration. A big part of this role is making hardware talk to software: connecting instruments, robotics, and scheduling systems into a coherent whole. A genuine interest in biology. No background required, but our product is running biology experiments in the physical world and that should excite you. High-autonomy, founder mindset. We share context and vision openly. You figure out what matters most and go work on it. Pragmatism. You care about solving the problem well, not about the stack or the tools. You write code primarily with AI, but you have enough experience writing software without it to know what good code and good architecture look like. Application deadline We are reviewing applicants on a rolling basis. Find more English Speaking Jobs in Switzerland on Arbeitnow

Adaptyv is building an automated lab that lets AI agents run biology experiments. We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world. We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today. Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development. We're growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation. About the Role You'll build work-cell orchestration, instrument drivers, protocol scheduling, error-recovery logic, and monitoring. Physical systems fail in ways pure software doesn't — a plate gets stuck, a liquid handler skips a well, a temperature controller drifts. Your job is to make the system handle all of it gracefully. This is a broad, hands-on role for a strong engineer who wants their code to drive real machines and see it run the same day. What You'll Do Build orchestration software that coordinates liquid handlers, plate readers, incubators, and robot arms — handling timing dependencies, state, and error recovery. Reverse-engineer and develop instrument drivers and APIs. Each instrument speaks a different protocol (serial, USB, TCP/IP); you work out how it talks and build a clean abstraction over it. Model and execute complex multi-step protocols reliably — a single run can span dozens of steps across multiple instruments. Build error-recovery logic so that when something fails mid-run, the system retries, skips, alerts, or pauses depending on the failure mode. Create monitoring and observability for work-cell health: instrument status, run progress, error rates. Debug across the software–hardware boundary — figuring out whether bad data is a comms, firmware, calibration, or code problem. Work closely with lab automation engineers, the rest of the software team, and the scientists running production. Stack TypeScript and Python, Postgres (Supabase), Modal for compute. We control instruments with open-source Python tooling like PyLabRobot and PyHamilton wherever we can, rather than proprietary vendor GUIs. What We're Looking For Strong software engineering skills. You write production code in Python and/or TypeScript — well-structured and maintainable, not just prototypes. Comfortable at the hardware-software boundary. You've built software that drives physical devices, or you're excited to. You can read a protocol spec, debug a flaky connection, and reason about timing. Lab automation experience is a strong plus. Familiarity with PyHamilton, PyLabRobot, Opentrons, or similar tooling helps — as does a background in robotics, industrial automation, IoT, or embedded systems. Maker and hacker attitude. You like figuring out how closed systems work and building the thing that makes them work better. Bonus if you're comfortable with electronics, microcontrollers, or a 3D printer when an integration needs a physical fix. AI-native builder. It's 2026 — you build with coding agents like Claude Code as a default, and you have sharp judgment about what they produce. Self-starter and independent. You define what needs building from how the lab actually works, not just what's in the ticket. Reliability-minded. The lab runs 24/7; you design systems where one instrument failing doesn't cascade through the whole work cell. Biology background not required — but you should be excited that the code runs real experiments. Details Location: Lausanne, Switzerland (on-site — you need hands-on access to physical instruments). Type: Full time Start date: ASAP Application deadline We are reviewing applicants on a rolling basis. Find Jobs in Switzerland on Arbeitnow

About Us: DeepJudge is Switzerland's leading AI and ICT scale-up, transforming how law firms and legal departments access and leverage their knowledge. Founded by former Google search engineers with PhDs in AI from ETH Zurich, and backed by top-tier Silicon Valley investors, we are building the intelligence layer that powers the legal industry. Every firm can license the same AI models, but no two firms share the same institutional knowledge. Decades of experience, work product, and precedent are often trapped across systems, underused and inaccessible. DeepJudge makes this expertise instantly available through world-class enterprise search and AI infrastructure, enabling firms to automate workflows, build knowledge-powered applications, and turn experience into a lasting advantage. Our technology is trusted by many of the world's leading law firms, including Freshfields, Gunderson Dettmer, Holland & Knight, Arent Fox, and Cozen O'Connor. Headquartered in Switzerland with a growing team across North America, we are expanding rapidly and shaping the future of how professional knowledge is discovered and applied. At DeepJudge, we move fast, think rigorously, and care deeply about what we build. We combine cutting-edge research with close collaboration with our clients to deliver solutions that truly make an impact. If you want to be part of a team defining how AI transforms high-stakes knowledge work, this is the place to do it. About the role: As a Site Reliability Engineer at DeepJudge, you own the reliability of the systems that leading law firms depend on every day. We run our AI search platform in dedicated production environments, each a large-scale search and retrieval system operating at very high data volumes, alongside our ingestion pipelines and data stores, on container-orchestrated infrastructure across multiple public and private clouds. Keeping those environments fast, available, and trustworthy is a genuine engineering challenge, and it's your mission. This is a technical, infrastructure-focused role: you'll spend your time in systems, code, and telemetry. You'll harden the platform so that classes of failure can't recur, build observability and SLOs to let us see problems before they surface, plan capacity ahead of relentless data growth, and automate away the toil of safely operating many production environments. You'll work across our deployment and infrastructure-as-code and partner closely with product engineering to feed reliability learnings back into the platform. If you like operating serious distributed systems at scale and turning firefighting into engineered reliability, this role is for you. Your responsibilities will include: Owning the availability, latency and performance of our production environments: large-scale search and retrieval services, ingestion and data stores on container-orchestrated infrastructure across multiple public and private clouds Owning the cloud infrastructure across multiple public and private clouds, networking, identity and access, compute and storage, and managing cloud capacity, quotas and cost as the fleet grows Improving deployment and infrastructure through code: GitOps-based configuration and deployment and infrastructure-as-code across our public and private clouds, with safe, previewed, recoverable production changes Defining and instrumenting SLOs and error budgets and building the dashboards, metrics and alerting that make production observable and actionable Reducing operational toil through automation and internal tooling written in Python and / or Go Provisioning and standardizing new production environments to a defined reliability bar You're a great fit if you: Have 3+ years in SRE, production / platform engineering, or infrastructure-heavy software engineering, operating real production systems under reliability expectations Are strong at container-orchestration operations in production and comfortable on at least one major public cloud Have solid cloud infrastructure experience on a major public cloud and a working grasp of cloud capacity, quotas, and cost Practice observability hands-on with metrics, logs and traces, and use it to root-cause live incidents Work fluently with infrastructure-as-code and GitOps Can code in Python and / or Go for automation, tooling, and reading and patching service code. Bring sound production judgment and document your work clearly for other engineers Bonus: experience operating a large-scale search or distributed data system, database operations, dedicated / enterprise-deployed software, or AI / enterprise-search infrastructure in regulated domains What you can look forward to: Owning the reliability of systems that the world's leading law firms rely on: real scale, real impact Deep, hands-on work with modern infrastructure: distributed search at very large scale, container orchestration across multiple clouds, and a mature infrastructure-as-code and GitOps stack A rigorous, high-urgency engineering culture founded by ex-Google search engineers and ETH Zurich AI PhDs The chance to build the reliability discipline, SLOs, incident practice, automation, from a strong foundation, not inherit a rigid one A collaborative team in Zurich shaping how AI transforms professional knowledge work At DeepJudge, we believe great teams are built on diverse perspectives and experiences. We are proud to be an equal opportunity employer and are committed to fostering an inclusive, high-performance culture where everyone can thrive. We welcome applicants of all backgrounds and do not discriminate based on race, religion, color, national origin, gender, gender identity or expression, sexual orientation, age, marital status, disability, veteran status, or any other characteristic protected by law. If this role excites you, but you feel you don't meet every qualification, we encourage you to apply anyway and tell us why you'd be a great fit. Find more English Speaking Jobs in Switzerland on Arbeitnow

Fusionality is building the measurement, simulation and control stack of the fusion energy reactors of the future. Our technology enables effective and reliable operation, monitoring, and analysis of high-temperature plasmas in fusion devices — which will one day provide clean, practically limitless power to the grid. We have spun out of EPFL's Swiss Plasma Center and have just completed our pre-seed fundraise. We are looking for a Senior Control Systems Engineer to join our founding team in Lausanne and help build our core technology. This job is for you if you are a passionate engineer with deep knowledge cutting across real-time / embedded systems, software and hardware, and excited about building the systems to monitor and control real-world fusion plasmas. Tasks Implement real-time control, analysis, data acquisition systems in the kHz to MHz range, as individual contributor and in a team. Integrate solutions across a variety of company products and services as well as on our in-house test beds. Provide technical leadership within a growing real-time control and software engineering team that you will help to build. Translate customer needs into requirements and specifications. Requirements Experience taking hard-real-time acquisition and control loops from incomplete requirements through to commissioning on hardware, in domains such as automotive, robotics, embedded, electrical and/or scientific instrumentation. 'Full stack': familiarity with all aspects of real-time technologies, from physical/DAQ, real-time software frameworks and middleware, real-time OS and integration. Fluency in a mix of high-level and low-level languages such as C, C++, Rust, MATLAB/Simulink, Python. Obsession with code quality, testing and reliability. Experience with distributed real-time systems, real-time networking and field buses and/or SCADA is an advantage. Experience with embedded/μC/FPGA technologies and/or safety critical systems is an advantage. Benefits The unique opportunity to play a foundational role at a dynamic, fast-growing startup, shaping the technical solutions and products from the ground up. The opportunity to build cutting edge technology to monitor and control plasmas in real fusion devices, working side-by-side with leading plasma and control experts. Great working conditions, located in Lausanne, Switzerland, a city and country known for its high quality of life. Competitive salary and equity compensation and benefits including immigration assistance. If you are excited about joining our team, send your CV including information about a real-time system you have taken into operation. We're looking forward to hearing from you. Find Jobs in Switzerland on Arbeitnow

You want to help build Europe's resilience. You want to protect people and critical infrastructure - ultimately saving the lives of thousands. You want to work at the frontier of high-performance autonomous systems. At CDDS, you'll build the software platform that connects our next-generation interceptor drones with sensors and operators, the nervous system of a counter-drone defense network protecting critical infrastructure and, ultimately, saving lives. We're looking for a strong all-around software engineer to: Build the platform that fuses radar, sensors, and third-party data into a single, real-time operational picture Integrate our drones with external systems at low latency, under conditions where reliability isn't optional Design fleet-management tooling to monitor, configure, and coordinate drones operating in the field This is real-time, safety-critical software with actual physical stakes. You'll work close to hardware, close to operators, and close to the mission. We move fast and priorities shift as the threat landscape does. Tasks What you will own Architect the ground-segment platform that fuses radar and multi-sensor data into a real-time operational picture, under latency budgets where milliseconds decide outcomes Build the integration layer connecting our drones to third-party sensors and platforms, designing the plugins and data interfaces that make it work reliably in the field Design and own fleet-management and provisioning tooling that commands and coordinates a live interceptor fleet Profile, tune, and harden system performance so it holds up under real-world load Work close to the field: see your code deployed on real hardware, in front of real customers Requirements REQUIREMENTS MSc or PhD in Computer Science, Software Engineering, or a related technical field from a top-tier university, with an outstanding track record 3+ years of professional experience building production software, with deep, demonstrable Python expertise Fluency in Linux-based development environments Solid grounding in software security fundamentals NICE TO HAVE Experience integrating with command and control (C2) systems Experience working with radar feeds or other external sensors Knowledge of networking protocols and secure communication Comfort living in a bash CLI Benefits WHY CDDS Direct impact on a mission‑critical technology shaping Europe's security landscape Fast‑moving startup environment with high ownership Work with a highly technical, ambitious, and hands‑on team Real‑world testing, deployments, and customer demonstrations Attractive compensation DETAILS Location: Hardbrucke (Zurich), on‑site Start date: when you are ready Environment: Rapidly growing deep‑tech startup, high‑impact mission Find more English Speaking Jobs in Switzerland on Arbeitnow

EggAI · Full-time · Remote (EU & UK) The Role A very strong senior software engineer with deep, hands-on experience building and operating production systems. We hire for engineering strength first: people who write good software, reason about failure, and own what they ship. You will work in a team of 2 to 6 engineers on a client project . Clients come to us because we work at the forefront of AI in the enterprise; you help implement our AI strategy. AI experience is required. Much of our work involves LLM-powered and agentic systems, and while you may not be working directly on LLMs, you will be working on LLM based systems. What You'll Do Build and operate the production systems at the centre of the engagement, end to end — you own what you ship, including after it's reached production Lead architecture discussions for your part of the system, with the support of the wider team Take ownership: pick up the ambiguous problem, chase down the answer, and say so when something is going wrong Work directly with the client's engineers and with our project manager / product owner Work in a "normal" team rhythm — daily standups, planning, retrospectives, code and design review What We're Looking For 10+ years designing, building and maintaining production systems that real users depend on — clean testable code, sound API and data modelling, and the judgement to know which abstractions are worth it Production AI experience : You have built and operated GenAI systens in production with real users Has owned code in production — deployment, monitoring, on-call or equivalent — and can debug hard problems in live systems: concurrency, performance, data correctness Distributed systems fundamentals : services, queues, retries, idempotency, failure modes, and integrating third-party APIs that are not reliable Databases : schema design, query performance, migrations Operational rigour : meaningful automated testing, useful instrumentation, CI/CD and shipping incrementally Client-facing ability : has delivered against real business requirements and can hold a technical conversation with non-engineers Languages : Python (primary), TypeScript/JavaScript. Strong engineers coming from Go, Java, C#, Rust or similar who are willing to work in Python are in scope Infrastructure : cloud platforms (AWS/GCP/Azure), containerisation Desired qualities Depth — you can explain the systems you built and the trade-offs you chose Balances speed of iteration with production reliability Clear communicator, in writing as well as in conversation Learns new domains quickly and deliberately Interview Process Introductory call - 30 minutes Behavioural/Management interview - 60 minutes Technical interview (choice of walking through own code, live coding, or take home exercise) - 60 minutes Find more English Speaking Jobs in France on Arbeitnow

Location: Bristol, UK Start date: September 2027 Application deadline : Midnight, 29th November 2026 We encourage you to apply early, as we may close applications before the advertised deadline. The Graduate Programme at Graphcore Join Graphcore in a permanent role and start your career with two years of hands-on learning. From day one, you'll be trusted to take ownership, share your ideas and help shape what we're creating. You'll tackle challenging problems alongside a team who support your development and are as excited about your success as you are. What you'll work on Put your programming skills to work on the firmware that helps Graphcore products start up, communicate and run reliably. As a Graduate Firmware Engineer, you'll help design, develop and deliver firmware for Graphcore's next generation products. Working closely with our silicon and hardware teams, you'll contribute to software that supports hardware bootup, power control, telemetry and monitoring. You'll write firmware to Graphcore standards, review code, contribute to technical discussions and help investigate issues. You'll also work with continuous integration, build systems and Agile practices. Your team and support The Firmware team develops the software that powers Graphcore hardware and silicon. We are involved in the design of hardware and software interfaces. You'll work with engineers across teams through technical design discussions, code reviews, Agile ceremonies, and practical problem solving. Technical evidence and open discussion guide our decisions, with shared responsibility for product quality. You'll be encouraged to ask questions, challenge existing approaches and share ideas for making things better. Take responsibility for your work and speak up when you spot a problem or need support. From day one you'll contribute your ideas and help colleagues investigate firmware issues. How you'll learn and grow During the two-year programme, you'll build your understanding of how embedded software enables complex hardware systems through hands-on firmware development. Work on bootup, power management protocols, telemetry and monitoring, writing the code that manages how our hardware behaves. Investigating issues will build your problem-solving skills, while continuous integration and build systems will show you how firmware is checked and prepared for delivery. Code reviews and technical discussions with engineers across teams will help you develop your engineering judgement, explain your approach and learn how firmware fits into the wider system. What we're looking for Bachelor's/Master's degree in Computer Science, Electronic Engineering, Maths or a related field Introductory experience with C or Python An understanding of continuous integration, build systems and software packaging best practices An interest in real-time embedded software, verification or complex embedded platforms Curiosity about server architecture, device drivers, operating system kernel development or server firmware security Bring a willingness to learn, ask questions and contribute to technical discussions with colleagues across teams You can demonstrate these skills through coursework, a dissertation, personal or team projects, research, or other relevant experience. Tell us what you built or investigated, how you approached it and what you learned. Benefits Flexible working: Balance your work and personal life with greater flexibility Retirement planning support: Up to 5% matched pension Phantom equity: Share in Graphcore's success Workplace experience: Enjoy thoughtfully designed office spaces for collaboration, with free food and an on-site barista to support your day Peace of mind protection: Income protection and life assurance to provide financial security for you and your loved ones Electric Vehicle Scheme: Choose an electric vehicle and lease it through salary sacrifice Flexible benefits: Tailor your benefits package with a choice of additional options, including private medical insurance and dental cover Optional benefits: Dental cover, health cash plan, private medical insurance, cycle to work scheme, give as you earn We welcome people from all backgrounds and experiences and are committed to building an inclusive environment where everyone can do their best work. We're an equal opportunity employer and recognise that everyone brings different strengths and perspectives. If you need any adjustments during the interview process, just let us know - we're happy to support you. Sponsorship Applicants must already have the right to work in the UK for the full duration of the programme, without requiring visa sponsorship. We are unable to sponsor work visas for our Early Careers opportunities. Introduction to Graphcore At Graphcore, we're building next generation AI compute: from semiconductors and software to systems at datacenter scale. We are proud to be owned by SoftBank Group and work with other companies in the SoftBank family to deliver AI compute to customers working at the AI frontier. Starting your career here means working alongside people with different backgrounds and expertise, from AI researchers to chip designers and software engineers. You'll learn from each other, bring fresh ideas and help solve challenging problems together. How to apply and what to expect To apply, answer the application questions below and upload your CV and cover letter. We'll let you know the outcome of your application by early December at the latest. If successful, you'll be invited to complete a technical assessment. Candidates who reach the final stage will then be invited to attend in-person assessments in early spring. Ready to put your learning into practice? Start your career in a permanent Firmware Engineer role, with two years of hands-on learning through the Graphcore Graduate Programme. Apply now and help shape what comes next. Find Jobs in United Kingdom on Arbeitnow

Location: Bristol, UK Start date: September 2027 Application deadline : Midnight, 29th November 2026 We encourage you to apply early, as we may close applications before the advertised deadline. The Graduate Programme at Graphcore Join Graphcore in a permanent role and start your career with two years of hands-on learning. From day one, you'll be trusted to take ownership, share your ideas and help shape what we're creating. You'll tackle challenging problems alongside a team who support your development and are as excited about your success as you are. What you'll work on Put your technical foundations to work on the infrastructure solutions that keeps Graphcore's engineering teams connected, productive and secure. As a Graduate IS Engineer, you'll support infrastructure operations, investigate technical issues and contribute to projects that improve reliability, performance and security. Your work will span servers, storage, networking, cloud platforms, automation and monitoring. You'll learn how these systems support AI engineering at scale, building practical experience with Linux, Windows, scripting and infrastructure as code. It's a chance to see how the technology behind an engineering organisation works and help make it better. Your team and support The Infrastructure Solutions team designs, builds and supports the IT environments that help Graphcore engineers work at scale. The team spans on-premise infrastructure, cloud, networking, automation and security. You'll learn from experienced engineers through hands-on problem solving, planned projects and technical discussions. You'll take ownership of useful, well-scoped work early, with support as you build your knowledge and confidence. You'll gain hands-on experience as you rotate through our IS teams, including Cloud and Application Security, Cybersecurity Operations, Networking, Data Centre Operations and more. Along the way, Martinus and Peter will provide mentoring and support to help you build your skills, grow your confidence and take the next steps in your career. We use evidence, service impact and practical trade-offs to guide our decisions. You'll be encouraged to ask questions, challenge existing approaches and share ideas for making things better. Take responsibility for your work and speak up when you spot a problem or need support. How you'll learn and grow During the two-year programme, you'll build infrastructure skills by working on real operational issues and improvement projects. Investigating technical issues will help you develop a methodical approach to problem solving and understand how servers, storage, networks and cloud services fit together. Work on scripting, automation and infrastructure as code will give you practical ways to improve how infrastructure is managed. Working alongside experienced engineers will help you weigh up reliability, performance and security, explain your approach and understand how infrastructure decisions affect the teams who depend on these services. What we're looking for Bachelor's/Master's degree in Computer Science, Maths, Machine Learning, Data Science or a related field Familiarity with Linux or Windows server environments An understanding of networking fundamentals such as TCP/IP, DNS, routing or firewalls Introductory scripting experience with Python, Bash or PowerShell Bring an interest in infrastructure, cloud technologies, systems engineering or platform operations, and motivation to learn through practical problem solving. You can demonstrate these skills through coursework, a dissertation, personal or team projects, internships, hobbies or other relevant experience. Tell us what you built or investigated, how you approached it and what you learned. Benefits Flexible working: Balance your work and personal life with greater flexibility Retirement planning support: Up to 5% matched pension Phantom equity: Share in Graphcore's success Workplace experience: Enjoy thoughtfully designed office spaces for collaboration, with free food and an on-site barista to support your day Peace of mind protection: Income protection and life assurance to provide financial security for you and your loved ones Electric Vehicle Scheme: Choose an electric vehicle and lease it through salary sacrifice Flexible benefits: Tailor your benefits package with a choice of additional options, including private medical insurance and dental cover Optional benefits: Dental cover, health cash plan, private medical insurance, cycle to work scheme, give as you earn We welcome people from all backgrounds and experiences and are committed to building an inclusive environment where everyone can do their best work. We're an equal opportunity employer and recognise that everyone brings different strengths and perspectives. If you need any adjustments during the interview process, just let us know - we're happy to support you. Sponsorship Applicants must already have the right to work in the UK for the full duration of the programme, without requiring visa sponsorship. We are unable to sponsor work visas for our Early Careers opportunities. Introduction to Graphcore At Graphcore, we're building next generation AI compute: from semiconductors and software to systems at datacenter scale. We are proud to be owned by SoftBank Group and work with other companies in the SoftBank family to deliver AI compute to customers working at the AI frontier. Starting your career here means working alongside people with different backgrounds and expertise, from AI researchers to chip designers and software engineers. You'll learn from each other, bring fresh ideas and help solve challenging problems together. How to apply and what to expect To apply, answer the application questions below and upload your CV and cover letter. We'll let you know the outcome of your application by early December at the latest. If successful, you'll be invited to complete a technical assessment. Candidates who reach the final stage will then be invited to attend in-person assessments in early spring. Ready to put your learning into practice? Start your career in a permanent IT Infrastructure Engineer role, with two years of hands-on learning through the Graphcore Graduate Programme. Apply now and help shape what comes next. Find Jobs in United Kingdom on Arbeitnow

Location: Bristol, UK Start date: September 2027 Application deadline: Midnight, 29th November 2026 We encourage you to apply early, as we may close applications before the advertised deadline. The Graduate Programme at Graphcore Join Graphcore in a permanent role and start your career with two years of hands-on learning. From day one, you'll be trusted to take ownership, share your ideas and help shape what we're creating. You'll tackle challenging problems alongside a team who support your development and are as excited about your success as you are. What you'll work on Turn the models you've studied into AI systems that run at scale. In Applied AI, you'll help implement, train and optimise advanced models on Graphcore's next generation hardware, connecting research ideas with systems running across thousands of accelerators. You'll benchmark models, use profiling to find performance bottlenecks, design experiments and contribute fixes across models, software and accelerator systems. Working with Research, Software and Product teams, you'll test ideas that could inform future hardware. Your experiments will help us understand what makes a model accurate, efficient and ready to scale. Your team and support The Applied AI team acts as a proxy for Graphcore's customers. We understand current AI models, applications and software, then make sure Graphcore technology works at scale. You'll work alongside people who write low-level kernels, train large language models and enjoy figuring out challenging AI problems together. Work spans low-level kernel optimisation through to implementing research-level algorithms for new AI models. Engineers move between experiments, profiling, code reviews and technical debate – giving you a view of how different parts of an AI system fit together. Decisions are driven by evidence, performance data and clear engineering judgement. You'll be encouraged to ask questions, challenge existing approaches and share ideas for making things better. Take responsibility for your work and speak up when you spot a problem or need support. How you'll learn and grow During the two-year programme, you'll build technical range through hands-on work across AI models and accelerator systems. With visibility across the full stack – from novel accelerator hardware and its software stack to state-of-the-art AI applications – you'll identify opportunities to innovate and differentiate Graphcore's technology. What we're looking for Bachelor/Master's degree in Machine Learning, Computer Science, Maths, Data Science, or related field Software development skills and proficiency with a deep learning framework such as PyTorch or JAX An understanding of deep learning architectures, optimisation, evaluation and scaling, with the ability to design, run and explain ML experiments A collaborative approach and willingness to work through unfamiliar technical problems, ask questions and take responsibility You can demonstrate these skills through coursework, a dissertation, personal or team projects, research, or other relevant experience. Tell us what you built or investigated, how you approached it and what you learned. Benefits Flexible working: Balance your work and personal life with greater flexibility Retirement planning support: Up to 5% matched pension Phantom equity: Share in Graphcore's success Workplace experience: Enjoy thoughtfully designed office spaces for collaboration, with free food and an on-site barista to support your day Peace of mind protection: Income protection and life assurance to provide financial security for you and your loved ones Electric Vehicle Scheme: Choose an electric vehicle and lease it through salary sacrifice Flexible benefits: Tailor your benefits package with a choice of additional options, including private medical insurance and dental cover Optional benefits: Dental cover, health cash plan, private medical insurance, cycle to work scheme, give as you earn We welcome people from all backgrounds and experiences and are committed to building an inclusive environment where everyone can do their best work. We're an equal opportunity employer and recognise that everyone brings different strengths and perspectives. If you need any adjustments during the interview process, just let us know - we're happy to support you. Sponsorship Applicants must already have the right to work in the UK for the full duration of the programme, without requiring visa sponsorship. We are unable to sponsor work visas for our Early Careers opportunities. Introduction to Graphcore At Graphcore, we're building next generation AI compute: from semiconductors and software to systems at datacenter scale. We are proud to be owned by SoftBank Group and work with other companies in the SoftBank family to deliver AI compute to customers working at the AI frontier. Starting your career here means working alongside people with different backgrounds and expertise, from AI researchers to chip designers and software engineers. You'll learn from each other, bring fresh ideas and help solve challenging problems together. How to apply and what to expect To apply, answer the application questions below and upload your CV and cover letter. We'll let you know the outcome of your application by early December at the latest. If successful, you'll be invited to complete a technical assessment. Candidates who reach the final stage will then be invited to attend in-person assessments in early spring. Ready to put your learning into practice? Start your career in a permanent Machine Learning Engineer role, with two years of hands-on learning through the Graphcore Graduate Programme. Apply now and help shape what comes next . Find more English Speaking Jobs in United Kingdom on Arbeitnow

Location: Bristol Start date: September 2027 Application deadline: Midnight 29 th November We encourage you to apply early, as we may close applications before the advertised deadline. The Graduate Programme at Graphcore Join Graphcore in a permanent role and start your career with two years of hands-on learning. From day one, you'll be trusted to take ownership, share your ideas and help shape what we're creating. You'll tackle challenging problems alongside a team who support your development and are as excited about your success as you are. What you'll work on Put your engineering knowledge to work on how advanced AI hardware moves from design into manufacture. As a Manufacturing Operations Graduate, you'll support silicon packaging and printed circuit board assembly production in Taiwan. You'll analyse performance data and use test design to investigate hardware and software issues, helping improve quality, cost and delivery. You'll also contribute to quality planning, audits and process control, alongside component selection and bill of materials management. Your team and support You'll join Manufacturing Operations in Bristol, working alongside Product Test, Quality and Supply Chain. Colleagues across the UK, Taiwan and India collaborate with design teams and development partners to solve manufacturing challenges. Experienced engineers and operations specialists will support you as you contribute to decisions guided by data and customer requirements. Bring your questions and ideas, listen to other perspectives and explore better ways of doing things. Take responsibility for your work and speak up when you spot a problem or need support. How you'll learn and grow During the two-year programme, your graduate rotation will show you how engineering decisions affect the finished product and its journey through a global supply chain. You'll develop the judgement to compare approaches and weigh up trade-offs, alongside project management and communication skills as you organise your work and explain your findings. What we're looking for Bachelor's/Master's degree in Mechanical or Electrical Engineering, Physics or a related field Knowledge of semiconductor design and manufacturing principles, and an understanding of design and manufacturing principles for printed circuit board assemblies and servers Experience using tools such as Python, Linux, Bash and Git Data analysis skills, with the ability to explain findings and support decisions using evidence You can demonstrate these skills through coursework, a dissertation, laboratory work, research, personal or team projects, or other relevant experience. Tell us what you built or investigated, how you approached it and what you learned. Benefits Flexible working: Balance your work and personal life with greater flexibility Retirement planning support: Up to 5% matched pension Phantom equity: Share in Graphcore's success Workplace experience: Enjoy thoughtfully designed office spaces for collaboration, with free food and an on-site barista to support your day Peace of mind protection: Income protection and life assurance to provide financial security for you and your loved ones Electric Vehicle Scheme: Choose an electric vehicle and lease it through salary sacrifice Flexible benefits: Tailor your benefits package with a choice of additional options, including private medical insurance and dental cover Optional benefits: Dental cover, health cash plan, private medical insurance, cycle to work scheme, give as you earn We welcome people from all backgrounds and experiences and are committed to building an inclusive environment where everyone can do their best work. We're an equal opportunity employer and recognise that everyone brings different strengths and perspectives. If you need any adjustments during the interview process, just let us know - we're happy to support you. Sponsorship Applicants must already have the right to work in the UK for the full duration of the programme, without requiring visa sponsorship. We are unable to sponsor work visas for our Early Careers opportunities. Introduction to Graphcore At Graphcore, we're building next generation AI compute: from semiconductors and software to systems at datacenter scale. We are proud to be owned by SoftBank Group and work with other companies in the SoftBank family to deliver AI compute to customers working at the AI frontier. Starting your career here means working alongside people with different backgrounds and expertise, from AI researchers to chip designers and software engineers. You'll learn from each other, bring fresh ideas and help solve challenging problems together. How to apply and what to expect To apply, answer the application questions below and upload your CV and cover letter. We'll let you know the outcome of your application by early December at the latest. If successful, you'll be invited to complete a technical assessment. Candidates who reach the final stage will then be invited to attend in-person assessments in early spring. Ready to put your learning into practice? Start your career in a permanent Manufacturing Operations Graduate role, with two years of hands-on learning through the Graphcore Graduate Programme. Apply now and help shape what comes next. Find more English Speaking Jobs in United Kingdom on Arbeitnow