Foundation Model Leadership Applied AI Research & Systems
- Location: London UK (on-site preferred; remote with monthly visit possible)
-
Job Type: Full-time Senior
Compensation: 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 Youll 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 Were 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 youve built and optimized foundation-scale models and want real technical ownership in an ambitious AI start-up wed love to meet you...
Foundation Model Leadership Applied AI Research & Systems Location: London UK (on-site preferred; remote with monthly visit possible) Job Type: Full-time Senior Compensation: share options Our Client: VC-backed AI/ML start-up Work AuthorizationMust have the right to work in the UK or be able...
Foundation Model Leadership Applied AI Research & Systems
- Location: London UK (on-site preferred; remote with monthly visit possible)
-
Job Type: Full-time Senior
Compensation: 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 Youll 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 Were 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 youve built and optimized foundation-scale models and want real technical ownership in an ambitious AI start-up wed love to meet you...
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