C&D Talent Advisory
Senior ML Engineer
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Hiring via TechTree
This is a role that TechTree is recruiting for on behalf of one of its clients.
TechTree is an AI-driven recruitment platform working with high-growth companies.
When you apply, TechTree's AI Agent matches you not just to this role, but to other relevant opportunities across its network, so one application can unlock multiple roles.
Senior ML Engineer | Foundation Models & CUDA
TechTree's client is hiring a Senior ML Engineer to help build and scale a novel foundation model for automated software delivery in embedded systems.
This is a deeply technical role for an engineer who has built large-scale foundation models, developed custom CUDA kernels, and scaled distributed ML systems in production.
Location: London — On-site
Employment: Full-time
Estimated compensation: £100,000–£150,000/year + equity
Level: Mid-Senior / Senior
What you'll own
- Lead development and production deployment of a large-scale foundation model
- Design and implement custom CUDA kernels for performance-critical workloads
- Optimise training and inference across GPUs and distributed infrastructure
- Architect scalable ML systems with demanding reliability and performance requirements
- Profile and improve data pipelines, training loops, inference, and serving infrastructure
- Evaluate modern architectures including Mixture-of-Experts and state-space models
- Build internal tooling, benchmarks, evaluation systems, and observability infrastructure
- Work closely with founders on technical strategy and optimisation priorities
- Improve model quality, latency, scalability, and compute efficiency
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What we're looking for
- Deep professional experience with CUDA C/C++
- Strong Python skills
- Experience building and shipping large-scale foundation models
- Proven custom CUDA kernel development
- Experience with distributed training and inference
- Strong knowledge of modern deep learning architectures
- Production expertise with PyTorch or another major ML framework
- Experience operating ML workloads on AWS, Azure, or GCP
- Strong understanding of ML observability, evaluation, and production SLOs
- Experience delivering complex systems in fast-moving environments
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Strong advantages
- Built a foundation model from 01
- Early-stage AI startup or top-tier research lab experience
- Experience with MoE, state-space models, and advanced inference optimisation
- Built tooling that significantly improved engineering or research productivity
- Experience optimising large-scale GPU workloads for cost and performance
Why consider this opportunity?
- Work on a genuinely novel foundation-model problem
- Significant technical ownership from day one
- Direct influence over architecture and ML strategy
- Work closely with an experienced founding team
- Competitive compensation plus equity
If this sounds like a fit, we'd love to hear from you. Apply today!
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