AI Research Engineer in Cambridge

A non‑profit membership organisation backed by UK Government and private funding, built around collaborative engineering for the safe and responsible development of foundational AI technologies. Bringing together startups, enterprises, public sector bodies and academia to co‑develop and deploy innovative AI systems. They’re building an AI lab with multiple GPU clusters and are looking for a skilled foundation model engineer with end‑to‑end experience across the full AI lifecycle from model development and data pipelines through to scalable deployment.

What You’ll Do

• Design and implement LLM training pipelines;
• Source and preprocess datasets;
• Fine‑tune and optimise open weight models (LLMs, vision, or traditional ML);
• Build evaluation frameworks;
• Develop and maintain data pipelines and training workflows;
• Optimise for latency, cost and scalability;
• Experiment with modern AI tooling.

Requirements

• Proven experience training and fine‑tuning LLMs or multimodal models (beyond API usage)
• Strong grasp of model evaluation, bias/variance tradeoffs, and data quality
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow)
• Experience building and maintaining ML pipelines in production
• Familiarity with GPU usage and optimisation

Nice to have

• Distributed training, large‑scale data processing, MLOps tooling, applied research background, or experience with retrieval systems and embeddings.
• A maths or computer science background with a focus on novel algorithms or techniques is a plus, as is industry experience in a large organisation or high‑growth startup.

Competitive salary and pension. High‑impact role in a growing organisation. Broad networking across tech and academia. Vibrant office based near Cambridge station.