Founding ML Systems Engineer, Distributed Training

Dex; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

Dex is partnering with a company that builds foundation models for physics, semiconductors, aerospace, defense, and fusion energy. You’ll be the first dedicated engineering owner for the ML stack, turning prototypes into robust code and building in-house tooling for experiment tracking and hyperparameter optimisation.

You’ll also add distributed training capabilities, own the backend platform delivering these models to customers, and define the engineering culture from day one.

Qualifications

• Senior, hands-on engineer who still ships critical code.
• Proven PyTorch experience across model code, data pipelines, and training loops.
• Experience with distributed training and multi-GPU/cluster setups.

Responsibilities

• Own the entire ML stack: model code, training workflows, and experiment infrastructure.
• Build distributed training capabilities for large-scale model development.
• Integrate independently developed research branches into a production-ready codebase.
• Design and build the backend platform that delivers these foundation models to customers.

Skills

PyTorch

Distributed training

Python backend

Model engineering

Docker/Kubernetes/IaC

Tools

Docker

Kubernetes

IaC

Job description

Dex is partnering with a company that builds foundation models for physics, semiconductors, aerospace, defense, and fusion energy. You’ll be the first dedicated engineering owner for the ML stack, turning prototypes into robust code and building in-house tooling for experiment tracking and hyperparameter optimisation.

You’ll also add distributed training capabilities, own the backend platform delivering these models to customers, and define the engineering culture from day one.