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Who we are: We're one of Europe's fastest-growing fintech companies – on a mission to create the world's most empowering way to pay. We launched the product in 2020 and achieved double unicorn status, valued at $2 billion, and since then have taken on more than 6 million customers. Our mission is to become the best way to pay for anything, anywhere and say goodbye to credit costs for everyone. This is huge. Want to join us? About the Role. We are seeking a talented and experienced Senior Data Scientist to join Zilch's Risk team, with a focus on developing and optimising advanced models in the Risk space, primarily across credit risk, with additional focus on collections optimisation and fraud detection. You will leverage diverse data sources to support key areas across the business, building production-grade models and decisioning solutions that improve risk outcomes, customer experience, and operational efficiency. This role will involve close collaboration with cross-functional teams, including product managers, engineers, risk strategy, credit, collections, fraud, and other data scientists, to ensure data-driven insights are successfully integrated into product strategies, risk decisioning, and business growth initiatives. This is a hands-on role for someone who combines strong applied machine learning with modern ML Ops practices. We are looking for a data scientist who can take models from exploration through to production, monitoring, and iteration. Key Responsibilities. Work with large and complex datasets to solve a wide array of challenging problems using various analytical and statistical approaches. Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve millions of customers and thousands of merchants. Build, validate, deploy, and monitor robust, scalable machine learning models and model pipelines across the risk lifecycle, including onboarding, affordability, life-time value, credit/default risk, in-life risk, collections, and fraud. Present complex data science findings and methodologies to senior stakeholders clearly and concisely. Apply machine learning methods to solve risk and product-related business problems and enhance our decision-making processes. Contribute to the team's coding efforts, ensuring best practices in version control, testing, CI/CD, model deployment, monitoring, methodologies, workflows, and tooling. Conduct A/B testing, champion/challenger testing, and experimental analyses to evaluate new features, risk strategies, model changes, and product changes. Partner closely with engineering and platform teams to operationalise models, automate workflows, and improve model reliability in production. What We're Looking For. 3+ years of hands-on experience as a data scientist, with a focus on building and deploying models to enhance the customer product experience, risk decisioning, and business outcomes, ideally within credit risk, collections, fraud, financial services, lending, payments, or another decision-intensive domain. Proficiency in SQL, Python and core data science and machine learning libraries, such as NumPy, Pandas and Scikit-Learn. Strong practical experience with machine learning model development, deployment, monitoring, and iteration in production environments, including cloud-based model training, archiving, serving, endpoint deployment, and tools such as Amazon SageMaker or similar. Experience communicating complex ideas to non-technical audiences and senior stakeholders. Strong understanding of machine learning methods, their application in real-world scenarios and a keen awareness of their limitations. A strong engineering mindset, with the ability to write clean, maintainable, production-ready code, use version control systems such as Git, and collaborate effectively in a multi-developer environment. A results-driven approach, with the ability to quickly iterate and improve models in production. Knowledge of AI safety considerations, such as bias detection, privacy management, and handling personally identifiable information (PII). Familiarity with software development best practices and continuous integration/continuous delivery (CI/CD) pipelines, such as GitHub Actions. Experience using DBT for data modelling and Looker for BI reporting. An interest in staying up to date with evolving technologies and applying them to enhance business outcomes. Nice to Have. The following are bonuses rather than strict requirements. We do not expect candidates to have all of them: Prior experience in credit risk modelling, collections optimisation, fraud detection, or risk strategy. Familiarity with risk model governance, explainability, fairness, affordability, or regulatory considerations in financial services. Experience with decision science, automated decisioning systems, decision engines, or risk strategy implementation. Experience applying neural networks or deep learning approaches to practical risk, fraud, or decisioning problems. Find more English Speaking Jobs in United Kingdom on Arbeitnow

Staff Product Manager, Product Discovery Engine About Us Constructor powers product search and discovery for some of the largest retailers in the world. We serve billions of requests every week, and you've probably seen our results somewhere and used our product without knowing it. We differentiate ourselves by focusing on metrics over features, and reinventing search and discovery from the ground up as a machine learning challenge with the specific goal of improving metrics like revenue. We're approximately doubling year over year despite the market slowing down and have customers in every eCommerce vertical. We're a passionate team of technologists who love solving problems and want to make our customers' and coworkers' lives better. We value empathy, openness, curiosity, continuous improvement, and are excited by metrics that matter. We believe that empowering everyone in a company to do what they think is best can lead to great things. Job Summary We're looking for a systems-minded Staff Product Manager to take Constructor's search and discovery to the state of the art — and keep it there — across every retail industry we serve. This is a highly technical, high-leverage role at the core of our Product Discovery Engine chapter: the teams responsible for how we retrieve, understand, and rank the right products for every shopper, on every query, for every customer. Your job is to raise discovery quality and, through it, our customers' business metrics. You won't be measured on features shipped — you'll be measured on relevance and business outcomes, like conversion, revenue per visit, and search-attributed GMV, moving up. You'll start embedded with our Search Quality team, owning its strategy and roadmap and getting deep into the systems that decide what shoppers actually see. Over time, your mandate grows to setting direction for the entire Product Discovery Engine chapter — deciding where we're heading and why across recall, ranking, query understanding, personalization, and the ML infrastructure underneath. This is a Staff role today with a clear path to Director as you take on chapter-wide leadership. Search at Constructor is fundamentally a machine learning problem, so this role lives and breathes ML. You'll partner closely with ML, data science, and engineering to turn the latest research into production wins, keep us ahead of both commercial competitors and academic state of the art, and be the connective tissue that aligns multiple teams — ML Recall, ML Infra, and, over time, teams like CORE, SABR, and Catalog Management — behind a single, coherent vision for great discovery. If you're excited about driving innovation across dozens of the world's largest retailers, being held to relevance and business outcomes, and pushing an already best-in-class product further ahead, this role is for you. What You'll Do Own business impact, not features. Drive measurable lift in search-attributed conversion, revenue per visit, and GMV alongside relevance across our customer base. Deliver across every retail industry. Move quality and business metrics across all the verticals we serve, accounting for the differences in catalog, language, and shopper intent. Keep us at the state of the art. Continuously translate the latest ML / IR research and competitive moves into production wins, and ship SOTA ML / LLM-assisted capabilities that beat our previous best on relevance. Set chapter vision and strategy. Define the multi-quarter direction for the Product Discovery Engine — where we're heading and why — tie it directly to customer business outcomes, and rally teams behind it. Lead Search Quality first. Own its strategy and roadmap, driving measurable improvements in the relevance and correctness of results. Orchestrate across the pipeline. Unify recall, ranking, query understanding, and personalization behind one definition of quality and one set of business metrics, so improvements compound instead of colliding. Turn ML research into production wins. Partner deeply with ML and data science to take models — from candidate generation and recall to LLM-assisted interpretation — from idea to production, balancing accuracy, latency, and cost. Make quality measurable and explainable. Build the metrics, evaluation frameworks, and tooling the whole chapter uses to measure, attribute, and explain discovery quality and its business impact. Own quality under pressure. Lead investigation and triage when issues arise, and design durable, systemic fixes rather than one-off patches. Grow the mandate. Expand into chapter-wide leadership spanning ML Recall, ML Infra, and — over time — teams like CORE, SABR, and Catalog Management. What Success Looks Like Within your first year, you will have: Driven measurable lift in search-attributed conversion and revenue per visit — moving business metrics, not just quality metrics. Driven measurable business-metric lift (conversion, revenue per visit, GMV) and relevance lift across every major retail vertical we serve . Shipped at least one state-of-the-art ML / LLM-assisted capability into production that beats our previous best on relevance. Won head-to-head quality benchmarks against every major competitor in the verticals we compete in, with a repeatable, defensible methodology. Taken core quality metrics to best-in-class levels and kept them improving quarter over quarter. Stood up an evaluation framework and tooling that ties model and system investments directly to customer business outcomes . What We're Looking For Extensive product management experience (typically 8+ years) in search, discovery, ML, or NLP-heavy products, including time operating at a senior or staff level. A track record of moving business metrics at scale — conversion, revenue, engagement — not just shipping features, and of setting strategy across multiple teams. Deep understanding of the end-to-end search pipeline: query interpretation → recall / candidate generation → ranking → reranking → personalization → delivery. Strong ML product depth — owning production models and reasoning about tradeoffs between high-capacity (LLM / batch) and low-latency (real-time) approaches — and a habit of staying current with state-of-the-art research. Fluency with retrieval and recall, query understanding (tokenization, synonyms, spelling correction, multilingual support), and search evaluation frameworks. A rigorous, measurement-first mindset that ties every quality investment back to business outcomes. Excellent cross-functional leadership — able to align teams with different goals behind a shared definition of quality and a shared set of business metrics, working shoulder-to-shoulder with engineering, data science, and ML Ops. Comfort operating with ambiguity, setting direction where none exists yet, and leading through clarity and credibility rather than the org chart. Benefits Unlimited vacation time — we strongly encourage all of our employees to take at least 3 weeks per year. A competitive compensation package including stock options. Company-sponsored US health coverage (100% paid for employee). Fully remote team — choose where you live. Work-from-home stipend! We want you to have the resources you need to set up your home office. Apple laptops provided for new employees. Training and development budget for every employee, refreshed each year. Parental leave for qualified employees. Work with smart people who will help you grow and make a meaningful impact. This position is fully remote — Constructor.io is a remote-first company. Diversity, Equity, and Inclusion at Constructor At Constructor.io we are committed to cultivating a work environment that is diverse, equitable, and inclusive. As an equal opportunity employer, we welcome individuals of all backgrounds and provide equal opportunities to all applicants regardless of their education, diversity of opinion, race, color, religion, gender, gender expression, sexual orientation, national origin, genetics, disability, age, veteran status or affiliation in any other protected group. How we handle your data. By submitting this application, you acknowledge that Constructor will collect and process the personal data you provide for the purpose of evaluating your candidacy for this role. If you are not selected, we will retain your data for a limited period as described in our Recruitment Privacy Notice . After that period your data will be deleted or anonymized. 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Anstellungsdetails Permanent Contract, Full- or Part-Time, Remote or Cologne / Düsseldorf / Darmstadt / Berlin Info Who we areWe are the tech powerhouse behind Kaufland's international online marketplaces and a company within the Schwarz Group. Driven by a start-up mentality and working on an equal footing within flat hierarchies, we develop the best marketplace solutions for our customers, sellers and partners. #FromEuropeForEurope Day by day, our Tech & Product Team of about 400 experts pursues the goal of creating the best possible customer shopping experience for our online marketplace. Through innovative technical developments, they not only create an outstanding shopping experience but also lay the foundation for an optimal selling experience for our sellers. Learn more about our division, areas, and cross-functional teams here ! Aufgaben Your tasks – this is what awaits you in detail You own and evolve the product strategy, vision, and roadmap for key B2B platform capabilities (Selling Experience or Marketing Technologies) on the Kaufland Global Marketplace You translate complex business requirements and seller insights into scalable, reliable, and high-impact digital product features You collaborate closely with Engineering, Architecture, Marketing, and Sales to build future-proof solutions and ensure seamless technical integrations You apply platform thinking to balance business goals, technical constraints, speed, scalability, and long-term ecosystem impact You utilize data, metrics, and user feedback to identify problems, measure performance, and continuously optimize seller adoption and growth You drive go-to-market strategies, product launches, and stakeholder communication to align cross-functional teams around shared priorities You conduct market and competitive analysis to proactively discover opportunities for product innovation and international marketplace expansion You explore and experiment with emerging technologies, AI-driven tools, and novel architectural/MarTech approaches to shape the future of our B2B platform Profil Your profile – this is what we expect from you You bring proven experience as a Product Manager owning products for sellers and partners: Technical platforms and tooling, AI-powered automation and service products, or marketing technology and growth products You have a strong builder mindset with a track record of driving products from early concept and architecture down to execution and delivery You build with emerging technologies and AI, from experimentation to production, driven by a curiosity for modern PM tools and innovative platform trends to shape the future of our B2B platform You possess a solid technical background with a clear understanding of APIs, data flows, system integrations, and web architectures You are highly data-driven and outcome-focused, knowing how to turn user data and performance metrics into actionable product decisions You possess outstanding stakeholder management and communication skills, with the ability to bridge technical complexity and business strategy You always put the customer first, bringing a passion for solving seller pain points and driving business impact You thrive in a fast-paced, pragmatic environment, bring fluent English skills (C1 level), and excel in an international, remote setup Benefits What we offer Create your own work-life balance: You have the flexibility to choose between working remotely (within Germany) or from one of our locations in Cologne, Darmstadt, Düsseldorf, or in Berlin! Urban Sports Club and RSG Group Fitness Studios : Get top deals for fitness, swimming, yoga and more Mental Well-Being: We support you on your well-being journey with special offerings such as Instahelp, the digital platform for online psychological counseling Vacation & Sabbatical: Enjoy 30 days of vacation per year and the opportunity to take a sabbatical once you have been part of the team for a certain period! Option for Pluxee restaurant vouchers : Buy Pluxee vouchers through us and benefit from tax-advantaged meal allowances! ' Deutschlandticket': We subsidise your train season ticket for more mobility Employee Discount: You will receive a monthly coupon for Kaufland.de Free choice of hardware: Mac or Lenovo, it's up to you Boost your growth: Benefit from our online language learning programs, diverse in-house training, and our automated 360-degree feedback This is who we are: Our dynamic culture combines flat hierarchies, a start-up mentality, an international team of over 65 nationalities, and the strength of the Schwarz Group to provide you an agile and secure working environment. We are team players : From day one, you will connect not only with your team but also with others through our digital onboarding journey , the buddy program , and regular team and company events, all-hands meetings, powerful mornings , and much more! Check out our Principles & our blog for even more insights into our company culture! Bewerben Diversity at Kaufland e-commerceWe welcome applications from everyone, regardless of skin colour, sexual orientation, gender identity, age, disability, ethnic origin, religion and ideology. We are signatories to the Charta der Vielfalt (German Diversity Charter) – because we know that extraordinary things can only be achieved with diversity. Read more here ! When applying, you can optionally include your pronouns in your resume. Why are you the perfect fit for this position? Don't bother with cover letters - we're interested in facts and figures! Feel free to share your Github profile with us in your application. As we have very international teams, we would highly appreciate it to receive your CV or profile link in English. We are looking forward to your application! Kaufland e-commerce Services GmbH & Co. KG Postal address: Habsburgerring 2 50674 Köln Ansprechpartner Your contact person: Verena Schilmann Find more English Speaking Jobs in Germany on Arbeitnow

🎤 Why voize? Because we're more than just a job! At voize, we believe the greatest gift to frontline workers is time - time to care, connect, and be present. Today, that time is lost to busywork and complex systems that pull them away from what matters most: people . Our vision is to change that by building AI companions that seamlessly take over digital workflows. We don't replace humans with technology - we amplify their impact. Our mission is backed with a $50M Series A funding led by Balderton Capital, with support from HV Capital, Y Combinator and other leading VCs. Today, 2,000+ facilities trust voize, and over 200,000 users rely on our AI companion to ease their daily workload. As a dynamic team, we combine first-in-class technology with meaningful social impact. And now, we're looking for you to join us on this mission! 💡 Your Mission: Turning Machine Learning capabilities into real user value voize is more than a scribe and far more than another documentation tool! We're defining & setting the benchmark what AI in healthcare actually looks like. As Product Manager - ML , you'll sit at the core of our product, you'll translate customer, Sales, and Customer Success signal into the ML product roadmap across our markets - defining what "better" means for our models, aligning stakeholders on priorities, and driving a shipping cadence that turns ML capability into measurable user value. 🚀 Your Daily Business - No two days are alike Own the ML product roadmap for core speech and NLP across our markets, turning field signal into clear priorities Run a structured customer-feedback → ML loop with Sales, Customer Support and Customer Success, and direct customer conversations (and close the loop back to the field) Define and maintain the model evaluation framework that gates releases (metrics, slices, thresholds, regression bar) Partner closely with Speech & NLP Leads as your roadmap counterparts to ship improvements to production Improve the product analytics and ML data integration: close the gaps between what we want to achieve, what we can measure in production, and what we train our models on. Own ML product KPIs (e.g., no-edit rate, documentation rate, edit rate per slot, transcription accuracy) and drive measurable improvements. 🤝 Your Skillset - What you bring to the table Extensive Experience in Product Management, background in speech recognition, NLP, or LLM-based product is a plus. Strong technical fluency in ML: evaluation, training data, latency/quality trade-offs, and release mechanics (you don't need to train models, but you do need to deeply understand them) Track record of shipping ML-powered products to production with measurable user impact Hands-on experience designing and operationalizing ML model evaluation frameworks Excellent communication in English; German is required to lead customer and end-user conversations (roughly B2) We are open to relocators, but this role is ideally based in Berlin and you'll work in a hybrid set-up. 🌱 Growing together - what you can expect at voize We are a fast-growing startup, that means you will tackle challenges, grow quickly, and make a real impact, giving frontline workers more time for people Become a co-creator of our success with a competitive s stock option program Generous perks: 30 vacation days plus your birthday off, Germany Transport Ticket, Urban Sports Club, regular company off-sites, and access to learning platforms such as Blinkist and Audible, plus free language courses You decide when you work best, that means flexible working hours and a good hybrid set-up, plus dedicated remote working days within the EU. ✨ Ready to talk? Apply now! 🚀 We look forward to your application and can't wait to meet you - no matter who you are or what background you have! Find more English Speaking Jobs in Germany on Arbeitnow

Education: Secondary (high) school graduation certificate. or equivalent experience. Work setting: Sales. Tasks: Promote sales to existing clients. Identify and solicit potential clients. Develop reports and proposals to illustrate benefits from use of good or service. Conduct sales transactions. Review and adapt information regarding product innovations, competitors and market conditions. Advertise and/or promote products, sales or services. Supervision: No supervision responsibility. Computer and technology knowledge: Presentation software. Salesforce. Electronic mail. Spreadsheet. Database management. MS Excel. MS Office. MS Outlook. Work conditions and physical capabilities: Fast-paced environment. Tight deadlines. Repetitive tasks. Attention to detail. Personal suitability: Client focus. Efficient interpersonal skills. Excellent oral communication. Excellent written communication. Organized. Reliability. Team player. Flexibility. Initiative. Positive attitude. Screening questions: Are you available to start on the date listed in the job posting?. Do you have experience working in this field?. Do you have the equipment you need to work from home (like internet and a workspace)?. Experience: 1 to less than 7 months. Other: Use of artificial intelligence. Workplace information: Remote.

About Us: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice: Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. ( blog ) Open source agents with frontier advisors: matching frontier performance through training and harness engineering. ( blog ) The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. ( blog) The Role AI Field Engineers at Fireworks are the technical tip of the spear. You embed with our most ambitious customers and technology partners to turn complex AI problems into production systems, fast. The role sits at the intersection of engineering, product, and customer delivery. You are hands-on-keyboard building POCs, MVPs, and production integrations, while also holding your own in executive-level conversations about architecture, strategy, and business outcomes. You spend most of your time building. You ship code, run benchmarks, debug production issues, and architect deployments. But you also lead discovery conversations, align stakeholders, and translate customer pain points into product improvements that compress the feedback loop from field to roadmap. This is a role for engineers who are comfortable on-site with customers, building the relationships and trust that happen in person, not just over a call. The Segment As a Field Engineer in the Enterprise track you will work with large organizations and digital-native companies adopting GenAI across the business. These engagements span more stakeholders and longer cycles, so you will manage executive relationships and align teams while staying hands-on in the code. The emphasis is on pairing strong technical delivery with the executive presence to earn trust across an org: discovery, solution design, POC execution, and the path to production at enterprise scale. What You'll Work On Technical Delivery and Deployment Build end-to-end POCs and MVPs alongside customer engineering teams, working inside their codebases, infrastructure, and constraints. For customers whose core product is built on GenAI, architect the inference foundations that capability depends on, and size deployments so they can scale in their market without infrastructure becoming the bottleneck. Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles, and tune deployments to hit those targets Deploy and validate new model families on inference frameworks (vLLM, SGLang), determining optimal shapes, quantization configs, and serving patterns across workloads. Model Strategy and Fine-Tuning Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation methodology. Build and run fine-tuning pipelines directly with customers, navigating trade-offs between model families, compute cost, and quality targets. Design and implement evaluation frameworks that measure production-quality metrics, not just benchmark scores. Customer Engagement and Stakeholder Management Many of our customers exist because of GenAI. Help them bake frontier model capabilities into their core offering and turn that into a durable competitive edge. Lead structured discovery conversations to unpack customer pain points, constraints, and success criteria before proposing solutions. Own the technical relationship from first engagement through production deployment. Earn trust with ML engineers and VPs in the same meeting. Spend time on-site with customers. Build trust and momentum in person, embedding with their teams where the work happens. Product Feedback and Platform Improvement Identify recurring customer pain points and translate them into concrete product proposals, working directly with engineering and product to ship fixes and features. Codify repeatable deployment patterns and contribute them back to internal tooling, documentation, and the platform itself. Feed customer signals (deployment patterns, failure modes, feature gaps) back into the product roadmap with specificity and urgency. What We're Looking For Minimum Qualifications 5+ years in a hands-on, customer-facing technical role: Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder. Demonstrated ability to build production software with customers, not just advise on it. You have shipped code running in someone else's production environment. Strong Python skills. Comfortable reading, writing, and debugging production code. Familiarity with Kubernetes and infrastructure engineering. Working knowledge of the LLM stack: inference trade-offs, model serving, fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus). Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure. Exceptional communication: able to run a sharp discovery call, present to a VP, and debug a latency issue with an ML engineer in the same afternoon. Preferred Qualifications 10+ years in technical field or engineering roles. Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM) and tuning deployments for real workloads. Experience operating as a technical authority inside a customer's environment building within their infrastructure, navigating their constraints, and shipping code that runs in their production systems. Track record taking GenAI POCs from prototype to production-scale deployments. Experience with hyperscaler AI platforms (Azure AI Foundry, AWS Bedrock/SageMaker, GCP Vertex). Experience building or integrating agentic systems, tool-use chains, or AI-native developer toolchains. Why Fireworks? Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. Build What's Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators. Find Jobs in United Kingdom on Arbeitnow

We design Spotify's consumer experience—end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints—from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify. You'll lead a senior-heavy group of 10–12 machine learning engineers, including Staff engineers, who team up dynamically to solve high-priority business problems while staying deep in content understanding (audio, video and text). This is a player-coach role with a strong strategic remit: you'll shape where the group goes next, grow our audio understanding expertise over the long term, and help the team scale through thoughtful, practical use of AI in everyday engineering work. What You'll Do Lead, coach and grow a group of 10+ senior and Staff machine learning engineers who team up dynamically around business problems while staying deep in their domain. Set technical and team strategy for multiple content understanding problems and turn it into clear, achievable plans. Own delivery of high-priority company initiatives, from shaping the problem through to measurable impact for listeners. Stay close to the technology as a player-coach. Lead technical strategy, reviewing designs, guiding modelling and retrieval choices, and contributing hands-on where it helps the team most. Define and champion a practical point of view on how ML engineers use AI tools in their day-to-day work, and help the team realise real productivity gains. Partner with product, design, research and other engineering leaders across Spotify to align priorities and share context. Who You Are You have deep machine learning expertise and Staff-level technical judgement, and you're comfortable getting hands-on when it matters. You bring experience across NLP, audio / music content understanding and recommender systems. You have a track record of managing engineering teams while delivering complex, cross-functional initiatives. You enjoy coaching senior and Staff engineers, and you help experienced people grow their impact. You have a clear, informed point of view on using AI to improve how ML engineers work, and you can inspire a team to adopt it. You think strategically, communicate clearly, and can balance long-term bets with near-term delivery. Where You'll Be This role is based in London or Stockholm. We offer the flexibility to work where you work best! There will be some in person meeetings, but still allows for flexibility to work from home. Find more English Speaking Jobs in United Kingdom on Arbeitnow

Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we're unlocking new possibilities as one global team. Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Global Engineering teams tackle complex technical challenges across a global, three-sided marketplace, building and scaling systems that serve millions of customers, riders and partners every day. We're looking for a Senior Machine Learning Engineer to join our London office as part of a Global DoorDash Engineering team (working hybrid, 3 days in the office). Our New Verticals team exists to grow monthly active usage outside of restaurant ordering — groceries, retail, and everything in between. That means turning someone who only orders restaurant food into someone who also uses the app for a grocery run, and turning dormant users into active ones. You'll work on the surfaces that make that happen: the homepage, vertical landing pages, and the notifications that bring people back. This role sits closer to the personalisation and ranking side of that mission, working alongside colleagues across DoorDash, Deliveroo and Wolt. What You'll Be Doing Build and improve ranking models for vertical landing pages (grocery, retail), deciding what a user sees first when they land on a store page Design models that blend new-vertical content into a homepage built around restaurant ordering, without disrupting the core experience Build personalisation models that translate a user's existing behaviour into relevant recommendations for verticals they haven't tried yet Contribute to notification targeting — who gets notified, with what message, and when, to drive adoption of new verticals What You'll Need to Thrive Minimum 5+ years of experience as an ML Engineer or Data Scientist, with a proven ability to write high-quality production code in Python Experience with end-to-end model productionisation A bias to simplicity, where you care most about achieving impact Background in personalisation, ranking, or recommender systems; exposure to causal inference or uplift modelling is a genuine plus but not expected Why Join Us? At Deliveroo, you'll do work that matters—solving real-world problems in a three-sided marketplace that's constantly evolving. We're food lovers, problem solvers, community builders and more, brought together by a shared drive to make things better. Working here you can expect to: 🔧 Solve meaningful problems at real scale Work on a complex, always-on marketplace that impacts millions every day. 🌱 See your impact, fast Ship, test and improve ideas quickly in a low-hierarchy, high-ownership environment. 🧠 Grow through challenge and ownership Take on big, ambiguous problems and accelerate your career with strong support. 🌎 A culture built for builders High standards, collaboration, flexible working and continuous learning. 💰 Share in the success you help create Competitive salary and equity options, so you're rewarded for the impact you make. ➡️ Want a deeper look at how we build? Check out our Tech Blog. Diversity, Equity and Inclusion At Deliveroo, we know that a great workplace reflects the world around us and that true diversity and inclusion make us stronger, more creative, and better at what we do. We're committed to fostering an environment where everyone can do their best work and feel they belong. We believe in equality of opportunity and welcome candidates from all backgrounds regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief. If you have a disability or long-term health condition and need support to apply for one of our roles, or require any reasonable adjustments during the recruitment process, you'll have the opportunity to let us know once you've submitted your application. We'll share details on how to request support so we can ensure you have a fair and equitable experience. If you're excited about making a real impact in a fast-moving marketplace and growing your career alongside ambitious, supportive teams, we'd love to hear from you! Beware of recruitment scams: DASH Brands will never ask you to pay money or share sensitive financial information during hiring — learn more about DASH Brands' legitimate recruiting process at careersatdoordash.com/recruitment-scam-awareness . Find Jobs in United Kingdom on Arbeitnow

Reddit is a community of communities. It's built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet's largest sources of information. For more information, visit www.redditinc.com . Location: Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands. The Ads Foundational Representations (AFR) team develops signals and representations of Reddit's core entities (ads, posts, users, and so on), capturing the semantic, contextual, and behavioral information that Reddit Ads needs. We work on building embeddings to understand content and users' interests based on the content they engage with. Our team has the potential to highlight one of Reddit's biggest differentiators: genuinely curated, high-quality, extremely relevant, and daily updated organic content. We are a Machine Learning/Data heavy team with a focus on the following areas: Multimodal & Content Embeddings - Make sense of organic (posts, comments, subreddits) and promoted (ads, shopping products, their landing pages) text and media content by embedding them into a shared space. Contextual and Behavioral Relevance - Working with Product & Data Science, establishing definitions of what ads are relevant to users and the content we show them next to, building metrics and fine-tuning embeddings to better reflect relevance. Knowledge Graph Embeddings - Building representations for the Knowledge graph entities, e.g., intellectual properties/brands, to be used for high-precision targeting & business insights. User Intent Modeling - Leveraging various techniques to introduce user representations based on the content they interact with: batch & real-time sequence modeling, LLM summarization, etc. LLM-based Representations - Leveraging LLMs, VLMs, and foundational models to build complex representations of Reddit entities that improve ranking outcomes The signals and features we create become a key piece in the Ads Delivery funnel, from targeting to the auction, as well as the Business Insights product and other advertiser-facing products such as Creative generation and optimization. As a Staff ML Engineer , you'll be in charge of setting the technical direction of multiple pillars the team owns. You will lead cross-functional ML projects end to end - from high-level business gap analysis to engineering execution. Roughly 50% of your time will be spent on technical leadership and mentorship (driving strategy & designs, cross-functional collaboration, raising the quality bar), another 50% being individual hands-on work (data analysis & engineering, modeling & automation). Responsibilities Providing technical leadership and mentorship to MLEs in the team: driving designs & their review, establishing best practices in analysis, modeling and engineering, keeping the bar high. Working closely with team/org leadership developing technical strategy for content-based embeddings & relevance for Ads. Developing new or iterating on existing embedding models for advertising use cases, ranging from aggregation pipelines to two-tower architectures and sequence models. Working with local and 3rd-party LLMs/VLMs: extract representations, develop evaluation methodologies, prompt tune and fine-tune large models to build state-of-the-art embeddings. Building data processing and inference pipelines for the models we develop. Qualitative and quantitative evaluation of the various features we develop, end-to-end experimentation from internal benchmarks to downstream recommender system offline metrics to online experiments. Ensuring the reliability, scalability, and performance of the ML systems by writing automated tests, monitoring performance, and implementing best practices for model management. Participating in modeling and coding reviews: You will review work by other team members and provide feedback to ensure that it meets the team's standards for quality and performance. Collaborating with cross-functional teams to understand business requirements and translate them into technical solutions. Required Qualifications: 7+ years of hands-on experience with the full lifecycle of designing, training, evaluating, testing, and deploying industry-level models. Demonstrated Staff-level technical leadership: mentoring engineers, driving standards and bar raising, leading complex cross-functional projects: from requirements, design to cross-team/functional alignment and execution without direct people-management authority. Excellent communication skills, with the ability to translate complex technical concepts to different audiences, both verbally and in writing. Strong track record of working on content rich NLP/CV problems at scale, and using embeddings as a tool to solve them. Established data-driven approach for ML system development. Excitement about working with data and readiness to look behind the metric numbers. Familiarity with the Ads domain and/or Search/Recommender systems. Experience with mainstream DL frameworks: PyTorch or TensorFlow. Preferred Qualifications: Experience with our stack (Python, Pytorch, Airflow, BigQuery, Ray, k8s, kafka, GCP) Tech leadership experience: mentoring junior engineers and leading complex projects. Hands-on experience with using/fine-tuning/building LLMs. Benefits: Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Group Personal Pension Scheme with Employer match Private Medical and Dental Scheme Income Replacement Programs Bike to Work scheme Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know. Find Jobs in United Kingdom on Arbeitnow

About ElevenLabs ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $22B - multiples of 11, always. We have expanded from voice into three main platforms: ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. How we work High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. Impact not job titles: We don't have job titles. Instead, it's about the impact you have. No task is above or beneath you. AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. Excellence everywhere: Everything we do should match the quality of our AI models. Global team: We prioritize your talent, not your location. What we offer Innovative culture: You'll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what's possible. Growth paths: Joining ElevenLabs means joining a dynamic team with countless opportunities to drive impact - beyond your immediate role and responsibilities. Learning & development : ElevenLabs proactively supports professional development through an annual discretionary stipend. Social travel : We also provide an annual discretionary stipend to meet up with colleagues each year, however you choose. Annual company offsite: Each year, we bring the entire team together in a new location - past offsites have included Croatia and Italy. Co-working : If you're not located near one of our main hubs, we offer a monthly co-working stipend. About the role We're looking for a Data Scientist - Product Analytics to join our Growth Data team. You'll own the analysis behind how people discover, adopt and stick with ElevenLabs' products, partnering closely with Product, Growth and the central Data team's certified metrics layer. Define and own product health metrics: activation, feature adoption, retention and engagement across ElevenCreative, ElevenAgents and ElevenAPI. Design, analyse and communicate the results of product experiments (A/B tests, feature launches, onboarding changes). Partner with Analytics Engineering on the certified product KPI layer in dbt, and with Product on turning ambiguous questions into trusted analysis. Work alongside fellow Growth data scientists on marketing- and revenue-adjacent questions that touch the product funnel. Requirements Demonstrated experience as a data scientist embedded with a product or growth team, ideally at a product-led company. Strong SQL and Python , with hands-on experience in experimentation (A/B testing) and product analytics. Ability to translate ambiguous product questions into clear, reusable analysis and defensible metrics. Comfort working directly with Product and Growth stakeholders , and pushing back on ill-defined asks. Structured thinker who can move fast without sacrificing rigour. Bonus Experience with activation / retention modelling or lifecycle analytics at a consumer or prosumer product. Experience with dbt or a modern warehouse, partnering directly with analytics engineers. Experience using AI tools or agents to speed up analysis or enable self-serve data access. Growth potential We believe in hiring the best talent in the world to make an impact in the right role at the right time. At ElevenLabs, strong performance creates opportunities for growth. Here are some of the career paths you can expect after excelling in this role: Grow into a Senior or Staff Product Data Scientist role as the Growth Data team scales. Expand scope across additional product lines (ElevenAgents, ElevenAPI). Path into a Growth Data Science lead or broader data leadership track. Location This role is remote-first. [please fill with specific location / timezone requirements]. #LI-Remote We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses. Find Jobs in Switzerland on Arbeitnow

🎤 Why voize? Because we're more than just a job! At voize, we believe the greatest gift to frontline workers is time - time to care, connect, and be present. Today, that time is lost to busywork and complex systems that pull them away from what matters most: people . Our vision is to change that by building AI companions that seamlessly take over digital workflows. We don't replace humans with technology - we amplify their impact. Our mission is backed with a $50M Series A funding led by Balderton Capital, with support from HV Capital, Y Combinator and other leading VCs. Today, 2,000+ facilities trust voize, and over 200,000 users rely on our AI companion to ease their daily workload. As a dynamic team, we combine first-in-class technology with meaningful social impact. And now, we're looking for you to join us on this mission! 💡 Your Mission: One source of truth for a company that runs on data As Senior Analytics Engineer , you own voize's company data from the warehouse to the dashboards. You'll be part of our Data & AI function - ensuring the data voize and our AI layer runs on are reliable, safe & scalable. The modern stack (Redshift, dbt, Fivetran, Lightdash) is already live: you make it rock-solid and turn it into the single source of truth the whole company runs on, from ARR to product adoption. As our first dedicated analytics hire, you partner directly with Finance, RevOps, Product, and Customer Success, turning their questions into numbers everyone trusts. 🚀 Your Daily Business - No two days are alike Model company data in dbt on Redshift: layered, tested, documented models built to outlive you Ship and run the company KPI dashboard in Lightdash, plus self-serve analytics for every team Own metric modeling and propose the definitions the whole company runs on. Sign-off sits with data leadership, and you make every number defensible Keep the ingestion layer running day to day (Fivetran connectors, existing ETL jobs), in close coordination with engineering Act as a partner to our teams and turn ambiguous business questions from Finance, RevOps, Product, and CS into trusted, self-serve answers Shape the data foundation before the function scales. As a Head of (Internal) Data & AI and a further Engineers join, you set the standards they inherit and go deeper on the architecture the whole company trusts. 🤝 Your Skillset - What you bring to the table 4+ years owning analytics from the warehouse onwards (modelling, reporting, BI) in production, ideally as an early or founding data hire Deep SQL above all, plus strong dbt (layered models, tests, CI, semantic / metric layers) A cloud data warehouse in production (Redshift ideal; Snowflake or BigQuery with willingness to switch) and a BI tool people actually use Business-facing autonomy: you partner with non-technical stakeholders, propose and defend metric definitions, and ship without waiting for a data team to form around you You document, test, and monitor by default, and finishing the 10% that makes a model trustworthy You know how to leverage AI, you have a track record of automating & building workflows with AI. 🌱 Growing together - what you can expect at voize We are a fast-growing startup, that means you will tackle challenges, grow quickly, and make a real impact, giving frontline workers more time for people Become a co-creator of our success with stock options We foster an open, collaborative culture with regular team events, whether you work from our Berlin office or remotely across Germany Generous perks: 30 vacation days plus your birthday off, Germany Transport Ticket, Urban Sports Club, regular company off-sites, and access to learning platforms such as Blinkist and Audible, plus free language courses You decide when you work best, that means flexible working hours and a good hybrid set-up. ✨ Ready to talk? Apply now! 🚀 We look forward to your application and can't wait to meet you - no matter who you are or what background you have! Find more English Speaking Jobs in Germany on Arbeitnow

About ElevenLabs ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $22B - multiples of 11, always. We have expanded from voice into three main platforms: ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. How we work High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. Impact not job titles: We don't have job titles. Instead, it's about the impact you have. No task is above or beneath you. AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. Excellence everywhere: Everything we do should match the quality of our AI models. Global team: We prioritize your talent, not your location. What we offer Innovative culture: You'll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what's possible. Growth paths: Joining ElevenLabs means joining a dynamic team with countless opportunities to drive impact - beyond your immediate role and responsibilities. Learning & development : ElevenLabs proactively supports professional development through an annual discretionary stipend. Social travel : We also provide an annual discretionary stipend to meet up with colleagues each year, however you choose. Annual company offsite: Each year, we bring the entire team together in a new location - past offsites have included Croatia and Italy. Co-working : If you're not located near one of our main hubs, we offer a monthly co-working stipend. About the role We're looking for a Data Scientist - Product Analytics to join our Growth Data team. You'll own the analysis behind how people discover, adopt and stick with ElevenLabs' products, partnering closely with Product, Growth and the central Data team's certified metrics layer. Define and own product health metrics: activation, feature adoption, retention and engagement across ElevenCreative, ElevenAgents and ElevenAPI. Design, analyse and communicate the results of product experiments (A/B tests, feature launches, onboarding changes). Partner with Analytics Engineering on the certified product KPI layer in dbt, and with Product on turning ambiguous questions into trusted analysis. Work alongside fellow Growth data scientists on marketing- and revenue-adjacent questions that touch the product funnel. Requirements Demonstrated experience as a data scientist embedded with a product or growth team, ideally at a product-led company. Strong SQL and Python , with hands-on experience in experimentation (A/B testing) and product analytics. Ability to translate ambiguous product questions into clear, reusable analysis and defensible metrics. Comfort working directly with Product and Growth stakeholders , and pushing back on ill-defined asks. Structured thinker who can move fast without sacrificing rigour. Bonus Experience with activation / retention modelling or lifecycle analytics at a consumer or prosumer product. Experience with dbt or a modern warehouse, partnering directly with analytics engineers. Experience using AI tools or agents to speed up analysis or enable self-serve data access. Growth potential We believe in hiring the best talent in the world to make an impact in the right role at the right time. At ElevenLabs, strong performance creates opportunities for growth. Here are some of the career paths you can expect after excelling in this role: Grow into a Senior or Staff Product Data Scientist role as the Growth Data team scales. Expand scope across additional product lines (ElevenAgents, ElevenAPI). Path into a Growth Data Science lead or broader data leadership track. Location This role is remote-first. [please fill with specific location / timezone requirements]. #LI-Remote We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses. Find Jobs in France on Arbeitnow