Founding ML Systems Engineer - Production-Ready Models

Dex

Greater London

On-site

GBP 120,000 - 160,000

Full time

3 days ago

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Job summary

Dex partners with a client that builds foundation models for physics and engineering. You’ll be the first dedicated engineering owner for the ML stack, turning research prototypes into robust code and delivering the backend tooling for customers.

You will own model code, training workflows, and distributed training, integrating research branches into a production-ready codebase while improving performance and scalability with PyTorch, Python, Docker, and Kubernetes.

Qualifications

Senior hands-on engineer who still writes and ships critical code.
Strong PyTorch experience across model code, data pipelines, and training loops.
Proven distributed training with multi-GPU/node setups and memory/communication considerations.
Model-engineering in physics/ simulation, vision, or LLMs with data-driven improvements.
Solid Python backend foundations: API design, orchestration, Docker/Kubernetes/IaC.

Responsibilities

Own the entire ML stack: model code, training/evaluation workflows, and experiment infra.
Build/distribute training capabilities for large-scale model development.
Integrate research branches into a production-ready codebase.
Profile bottlenecks to improve training stability and performance.
Design and build the backend platform delivering models to customers.