Founding ML Research Engineer - Hybrid, London | Equity

Generative Group; Greater London; Hybrid; GBP 140,000 - 160,000; Full time

Benefits offered by this job

Equity

Job summary

Generative Group is seeking a Founding Machine Learning Research Engineer to take research into robust engineering and scalable model training in London. You will directly train neural networks, optimize training loops, and build data pipelines across multiple GPUs.

You will work with AI researchers and domain experts in a fast-moving, early-stage environment. The role is office-based in London with limited focused home-working days, and a strong emphasis on practical collaboration and ambitious

Qualifications

• Direct experience training neural networks at scale with PyTorch.
• Experience with multi-GPU or multi-node training and performance optimization.
• Strong Python and production-quality software engineering practices.
• Typically six or seven-plus years' relevant experience in a mid-career role.
• High agency, rapid learning ability and comfort working in an ambitious early-stage team.

Responsibilities

• Train and optimise neural networks and build internal workflows and data pipelines.
• Improve training performance across GPUs and maintain experiment workflows.
• Work closely with AI researchers and domain specialists in a fast-moving early-stage environment.
• Contribute to model architecture, attention mechanisms, and evaluation or reproducibility practices.

Skills

PyTorch

Multi-GPU training

Python

Production-grade code

ML research

Tools

Git

Linux

Job description

Generative Group is seeking a Founding Machine Learning Research Engineer to take research into robust engineering and scalable model training in London. You will directly train neural networks, optimize training loops, and build data pipelines across multiple GPUs.

You will work with AI researchers and domain experts in a fast-moving, early-stage environment. The role is office-based in London with limited focused home-working days, and a strong emphasis on practical collaboration and ambitious