Buscar empleo: 50 ofertas de trabajo de distributed en Bath (julio 2026)

Senior Ml Engineer | London

hace 3 días

Bath

When you apply, our AI-powered matching platform considers you not only for this opportunity, but also for other relevant roles across our network, so one application can unlock multiple career opportunities. We only work with real companies hiring for live positions. Every opportunity on our platform is an active search. If there's a strong match, we'll guide you through the process. If not, we won't ignore you. Our Client is a venture-backed AI startup building a next-generation foundation model to enable fully autonomous software delivery for embedded control systems. This is an opportunity to join at an early stage, work directly with the founders, and help shape a technology designed to redefine how software is built, optimized, and deployed. London, United Kingdom (Remote with monthly office visits, ideally onsite) • Employment Type: Full-time, • Level: Mid‑Senior Level, • Compensation: £100,000-£150,000 + Equity (Share Options), • Work Authorization: Existing UK work authorization required We're looking for a Senior Machine Learning Engineer (Foundation Models) to lead the development, optimisation, and production deployment of our next‑generation foundation model. This is a deeply technical, hands‑on role where you'll architect large‑scale ML systems, optimise distributed training and inference, build GPU‑accelerated infrastructure, and work directly with founders to solve complex engineering challenges. If you're excited by cutting‑edge AI research, production‑scale machine learning, and building systems that push the limits of modern deep learning, we'd love to hear from you. • Lead the research, development, and deployment of large‑scale foundation models, • Define long‑term technical strategy for high‑performance ML systems, • Build scalable training and inference infrastructure, • Own model quality, performance, and reliability, • Optimise distributed training and inference pipelines, • Design GPU‑accelerated systems, including custom CUDA kernels when needed, • Profile and optimise data pipelines, training loops, inference, and deployment, • Build internal tooling, benchmarking systems, and evaluation frameworks, • Design scalable ML infrastructure and solution architectures, • Evaluate and implement state‑of‑the‑art ML technologies, • Work closely with founders to translate product goals into technical roadmaps, • Drive engineering excellence across the ML platform, • Extensive experience designing and building large‑scale foundation models, • Strong Python and CUDA C/C++ expertise, • Deep knowledge of PyTorch (preferred) or another major deep learning framework, • Experience optimising and debugging deep learning models, • Experience with distributed training and large‑scale inference, • Experience building ML systems on AWS, Azure, or GCP, • Strong GPU optimisation experience, • Experience building production ML infrastructure, • Excellent system design skills, • Delivery‑focused mindset with strong ownership, • Comfortable solving ambiguous, high‑impact problems, • Able to work onsite in London or visit the office at least once per month, • Experience with Mixture of Experts (MoE) or State Space Models, • Custom CUDA kernel development, • ML systems operating under strict production SLOs, • Experience building internal ML tooling and benchmarking frameworks, • Startup or research lab experience shipping foundation models, • Experience scaling distributed GPU clusters, • £100,000-£150,000 salary, • Meaningful equity (Share Options), • Opportunity to build a first‑of‑its‑kind foundation model, • Direct collaboration with founders, • No take‑home assignments or live coding interviews, • Transparent, low‑ego engineering culture, • High ownership and technical autonomy, • Office‑first environment with flexibility for exceptional candidates If you want to help build the next generation of foundation models and solve some of the hardest ML problems in production, we'd love to hear from you... #J-18808-Ljbffr

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