Senior ML Engineer | London
C&D Talent Advisory - AcademyGermany5 days ago
Full-timeRemote FriendlyEngineering, Information Technology
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Foundation Model Leadership | Applied AI Research & Systems
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
- 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
- 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
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
- 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)
- 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
- 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
- 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
Key Skills
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