Machine Learning Engineer | Cambridge | Consulting

The candidate should meet the following requirementsJob DescriptionRole DescriptionThe ideal candidate will haveAbout the role:

Join a specialist machine learning team working at the intersection ofdeep learning, model optimisation, and efficient deployment. You will help build and deploy advanced ML models forlow-latency speech recognition and foundation LLMs, focusing on reducing power consumption while maximising performance.

Your work will include:
Training state-of-the-art models on production-scale datasets.Compressing and optimising models for accelerated inference on modern hardware.Researching and implementing innovative ML techniques tailored for efficient deployment.Deploying and maintaining customer-facing training libraries.Yourinitial focus will be on speech recognition models, where you will:
Optimise training workflows for multi-GPU environments.Manage and execute large-scale training runs.Tune hyperparameters to improve both inference quality and performance.What you’ll be working on This is anend-to-end optimisation role, from algorithms through to deployment on modern silicon, with a mission to enablehigh-performance, low-power AI in production environments. You will work on deep technical challenges alongside engineers and researchers who care about efficiency, precision, and impact.

What they're looking for:Strong practical experience intraining deep learning modelsat scale.Knowledge ofoptimising ML workflowsfor multi-GPU environments.Experience withmodel compression, quantisation, and deploymentfor low-latency applications.Familiarity with frameworks such asPyTorch, TensorFlow, or similar.Ability totune models for real-world performance constraints.A collaborative mindset, able to contribute ideas and adapt to feedback in a small, high-trust team environment.Why join?Work on meaningful projects that contribute toreducing the energy footprint of global AI workloads.Collaborate in afriendly, multi-disciplinary teamthat values technical excellence, innovation, and open discussion.Develop your skills by working on cutting-edge optimisation challenges with a clear path from research to deployment.Enjoy a collaborative on-site culture with shared meals, games, and a supportive team environment, while retaining flexibility for hybrid working.