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Generative Group is seeking a Founding Machine Learning Research Engineer in London to guide the team’s work from research into robust engineering and scalable model training. This engineer-first role combines ML research with production-ready software practices, operating across PyTorch code, training loops, and performance optimisations.
You’ll train models, build data pipelines, and push systems to scale on large GPUs.
We are a low-profile, frontier AI research lab developing machine learning systems for extreme physics, including plasma physics and multispecies fluid dynamics. Our technology is designed to accelerate research and development across semiconductors, fusion energy, aerospace, defence and advanced engineering.
We build models from the ground up using high-fidelity simulation and experimental data, enabling faster and more reliable predictions across complex physical systems. Our mission is to create positive-impact AI that helps engineers and researchers explore more designs, parameters and operating conditions than traditional methods allow.
The company is seed-funded and has a small, highly technical team of AI researchers. We value scientific ambition, engineering excellence, rapid learning, direct communication, high agency and practical collaboration. This is an opportunity to help shape the foundations of a new category of AI alongside a high-calibre technical team.
As Founding Machine Learning Research Engineer, you will help take the team’s work from research into robust engineering and scalable model training. This is an engineer-first role with a strong machine learning research component—not a pure infrastructure or platform position.
You will directly train and optimise neural networks, build internal workflows and data pipelines, and improve training performance across multiple GPUs, currently up to approximately 20 GPUs in parallel. You will work across PyTorch model code, training loops, runtime behaviour, hardware utilisation and experiment workflows. Depending on your strengths, you may also contribute to model architecture, attention mechanisms, scientific machine learning and evaluation or reproducibility practices.
You will work closely with AI researchers and domain specialists in a fast-moving early-stage environment, making pragmatic technical decisions and turning promising ideas into reliable systems. The role is predominantly office-based in London, with limited focused home working possible.