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...