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CommonAI CIC

Foundation Model Engineer

Cambridge
Posted about 2 months ago
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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.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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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

Requirements

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

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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

Benefits

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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Skills

Foundation Model Engineering
LLMs
Multimodal Models
Data Pipelines
Model Evaluation
Python
ML Frameworks
PyTorch
TensorFlow
GPU Optimisation
MLOps
Feature Engineering
Distributed Training
Applied Research
Retrieval Systems
Embeddings

Location

Cambridge, England, United Kingdom

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