Senior ML Engineer | London

Foundation Model Leadership | Applied AI Research & Systems Location: London, UK (on-site preferred; remote with monthly visit possible) Job Type: Full-time | Senior Compensation: £100,000 – £200,000 + share options Our Client: VC-backed AI/ML start-up Work Authorization Must have the right to work in the UK or be able to obtain it On-site presence in London preferred Remote candidates must commit to at least monthly London visits Visa sponsorship not available About the Opportunity Our client is developing a novel foundation model to enable fully automated, unsupervised software delivery in embedded control systems. As a VC-backed, early-stage AI company based in West London, they are building the core ML stack from first principles. This is a hands-on technical leadership role focused on architecting, optimizing, and deploying large-scale foundation models in a high-urgency, high-impact environment. What You'll Do Lead research, development, and production deployment of the foundation model Define long-term technical strategy for high-performance ML systems Optimize models across diverse hardware environments Architect scalable distributed training and inference pipelines Build GPU-accelerated components, including custom CUDA kernels Profile and optimize the full ML stack end-to-end Create internal tooling, benchmarks, and evaluation harnesses Work closely with founders to translate product goals into technical roadmaps Tech Environment Python and CUDA C/C++ PyTorch (preferred) or similar deep learning frameworks Distributed training and large-scale inference systems Cloud platforms (AWS, Azure, or GCP) Modern foundation model architectures (MoE, state-space models) What We're Looking For Proven experience designing and implementing large-scale foundation models Strong hands-on performance optimization and debugging skills Practical experience with distributed training and inference Deep knowledge of modern deep learning frameworks Experience operating ML systems in production environments High urgency, ownership mindset, and comfort with ambiguity Nice to Have Custom CUDA kernel development Internal ML tooling or benchmarking experience Containerisation and orchestration exposure Embedded or control systems background Experience at top-tier AI/ML companies or research labs Why This Role Stands Out Ground-floor role shaping a novel foundation model Direct collaboration with founders High technical ownership and strategic influence Streamlined interview process (2 stages) Transparent, no-jargon engineering culture If you've built and optimized foundation-scale models and want real technical ownership in an ambitious AI start-up, we'd love to meet you...