When you apply our AI-powered matching platform considers you not only for this opportunity but also for other relevant roles across our network so one application can unlock multiple career opportunities.
We only work with real companies hiring for live positions. Every opportunity on our platform is an active search. If theres a strong match well guide you through the process. If not we wont ignore you.
About the Company
Our Client is a venture-backed AI startup building a next-generation foundation model to enable fully autonomous software delivery for embedded control systems.
This is an opportunity to join at an early stage work directly with the founders and help shape a technology designed to redefine how software is built optimized and deployed.
Location: London United Kingdom (Remote with monthly office visits ideally onsite)
Employment Type: Full-time
Level: Mid-Senior Level
Compensation: 00 Equity (Share Options)
Work Authorization: Existing UK work authorization required
About the Role
Were looking for a Senior Machine Learning Engineer (Foundation Models) to lead the development optimisation and production deployment of our next-generation foundation model.
This is a deeply technical hands-on role where youll architect large-scale ML systems optimise distributed training and inference build GPU-accelerated infrastructure and work directly with founders to solve complex engineering challenges.
If youre excited by cutting-edge AI research production-scale machine learning and building systems that push the limits of modern deep learning wed love to hear from you.
What Youll Do
Foundation Model Development;
Lead the research development and deployment of large-scale foundation models
Define long-term technical strategy for high-performance ML systems
Build scalable training and inference infrastructure
Own model quality performance and reliability
ML Infrastructure & Optimisation;
Optimise distributed training and inference pipelines
Design GPU-accelerated systems including custom CUDA kernels when needed
Profile and optimise data pipelines training loops inference and deployment
Build internal tooling benchmarking systems and evaluation frameworks
Architecture & Collaboration;
Design scalable ML infrastructure and solution architectures
Evaluate and implement state-of-the-art ML technologies
Work closely with founders to translate product goals into technical roadmaps
Drive engineering excellence across the ML platform
What Were Looking For
Must Have;
Extensive experience designing and building large-scale foundation models
Strong Python and CUDA C/C expertise
Deep knowledge of PyTorch (preferred) or another major deep learning framework
Experience optimising and debugging deep learning models
Experience with distributed training and large-scale inference
Experience building ML systems on AWS Azure or GCP
Able to work onsite in London or visit the office at least once per month
Nice to Have;
Experience with Mixture of Experts (MoE) or State Space Models
Custom CUDA kernel development
ML systems operating under strict production SLOs
Experience building internal ML tooling and benchmarking frameworks
Startup or research lab experience shipping foundation models
Experience scaling distributed GPU clusters
What We Offer
00 salary
Meaningful equity (Share Options)
Opportunity to build a first-of-its-kind foundation model
Direct collaboration with founders
No take-home assignments or live coding interviews
Transparent low-ego engineering culture
High ownership and technical autonomy
Office-first environment with flexibility for exceptional candidates
If you want to help build the next generation of foundation models and solve some of the hardest ML problems in production wed love to hear from you...
About the Hiring Process When you apply our AI-powered matching platform considers you not only for this opportunity but also for other relevant roles across our network so one application can unlock multiple career opportunities. We only work with real companies hiring for live positions. Every opp...
About the Hiring Process
When you apply our AI-powered matching platform considers you not only for this opportunity but also for other relevant roles across our network so one application can unlock multiple career opportunities.
We only work with real companies hiring for live positions. Every opportunity on our platform is an active search. If theres a strong match well guide you through the process. If not we wont ignore you.
About the Company
Our Client is a venture-backed AI startup building a next-generation foundation model to enable fully autonomous software delivery for embedded control systems.
This is an opportunity to join at an early stage work directly with the founders and help shape a technology designed to redefine how software is built optimized and deployed.
Location: London United Kingdom (Remote with monthly office visits ideally onsite)
Employment Type: Full-time
Level: Mid-Senior Level
Compensation: 00 Equity (Share Options)
Work Authorization: Existing UK work authorization required
About the Role
Were looking for a Senior Machine Learning Engineer (Foundation Models) to lead the development optimisation and production deployment of our next-generation foundation model.
This is a deeply technical hands-on role where youll architect large-scale ML systems optimise distributed training and inference build GPU-accelerated infrastructure and work directly with founders to solve complex engineering challenges.
If youre excited by cutting-edge AI research production-scale machine learning and building systems that push the limits of modern deep learning wed love to hear from you.
What Youll Do
Foundation Model Development;
Lead the research development and deployment of large-scale foundation models
Define long-term technical strategy for high-performance ML systems
Build scalable training and inference infrastructure
Own model quality performance and reliability
ML Infrastructure & Optimisation;
Optimise distributed training and inference pipelines
Design GPU-accelerated systems including custom CUDA kernels when needed
Profile and optimise data pipelines training loops inference and deployment
Build internal tooling benchmarking systems and evaluation frameworks
Architecture & Collaboration;
Design scalable ML infrastructure and solution architectures
Evaluate and implement state-of-the-art ML technologies
Work closely with founders to translate product goals into technical roadmaps
Drive engineering excellence across the ML platform
What Were Looking For
Must Have;
Extensive experience designing and building large-scale foundation models
Strong Python and CUDA C/C expertise
Deep knowledge of PyTorch (preferred) or another major deep learning framework
Experience optimising and debugging deep learning models
Experience with distributed training and large-scale inference
Experience building ML systems on AWS Azure or GCP
Able to work onsite in London or visit the office at least once per month
Nice to Have;
Experience with Mixture of Experts (MoE) or State Space Models
Custom CUDA kernel development
ML systems operating under strict production SLOs
Experience building internal ML tooling and benchmarking frameworks
Startup or research lab experience shipping foundation models
Experience scaling distributed GPU clusters
What We Offer
00 salary
Meaningful equity (Share Options)
Opportunity to build a first-of-its-kind foundation model
Direct collaboration with founders
No take-home assignments or live coding interviews
Transparent low-ego engineering culture
High ownership and technical autonomy
Office-first environment with flexibility for exceptional candidates
If you want to help build the next generation of foundation models and solve some of the hardest ML problems in production wed love to hear from you...