CommonAI CIC is a non-profit membership organisation, founded on a belief in collaborative engineering for the safe and responsible development of foundational AI technologies. A place where AI startups, enterprises large and small, public sector bodies and academia can share resources and knowledge, to codevelop and grow businesses, fast.

We are led by experienced founders, investors and engineers who believe that collaborative engineering drives faster AI innovation and are backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems.

The Opportunity

We’re seeking a highly skilled foundation model engineer who has experience of building, training, evaluating, and deploying LLMs or multimodal models end-to-end.

We are currently building an AI lab with multiple GPU clusters for testing new hardware and software technologies to accelerate machine learning and inference. This exciting role will primarily focus on model development, data pipelines and system performance. You’ll work across the full AI lifecycle, from experimentation to scalable deployment, with a strong emphasis on technical depth and rigour.

What You’ll Do

Design and implement end-to-end LLM training pipelines
Source and, where appropriate, preprocess datasets for training and evaluation
Fine-tune and optimise open weight models (LLMs, vision, or traditional ML)
Build evaluation frameworks and define performance metrics
Develop and maintain data pipelines and training workflows
Analyse training pipelines and optimise them for latency, cost, and scalability
Implement monitoring, logging, and feedback loops for continuous improvement
Experiment with modern AI tooling and services to investigate how they can be leveraged

Proven experience training and fine-tuning LLMs or multimodal models (not just using APIs)
Solid understanding of:

- Model evaluation and validation

- Overfitting, bias/variance tradeoffs

- Data quality and feature engineering

Proficiency in Python and ML frameworks (e.g. PyTorch, TensorFlow)
Experience building and maintaining ML pipelines in production
Familiarity with GPU usage and optimisation
Ability to debug and improve model performance systematically

We also value:

Knowledge of distributed training or large-scale data processing
Experience with MLOps tools (CI/CD for ML, experiment tracking, model versioning)
Background in applied research or publishing
Familiarity with retrieval systems, embeddings, or ranking models

Ideally you will have a maths or computer science research background with a focus on developing new algorithms or techniques for training and deploying AI models.

You may also have been working in industry in a large organisation or start-up with an emphasis on developing and deploying cutting edge machine learning.

When applying, please include:

Links to relevant projects, papers, or GitHub repositories
A brief description of a model/system you trained and deployed end-to-end

A collaborative and supportive work environment
The opportunity to have a high impact in a growing organisation
Competitive salary package and pension
Professional development opportunities
Networking opportunities with influential people from across the tech sector and academia
A vibrant office environment located a few minutes’ walk away from Cambridge train station

CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace.

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