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.

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