ML Researcher

You'll conduct original research in areas such as probabilistic models, active learning and Bayesian optimisation, while collaborating closely with other researchers and applied teams. The role blends academic-quality research with practical application, including contributions to product development and customer-facing research projects.

• PhD in Machine Learning, Statistics, Optimisation or a related field (or equivalent research experience)

• Track record of publications in ML, statistics or optimisation venues

• Experience or strong interest in:

• Probabilistic modelling (e.g. Gaussian Processes, Bayesian methods)

• Decision-making methods (Bayesian optimisation, bandits, RL, active learning)

Strong numerical programming skills (Python; NumPy; TensorFlow and/or PyTorch)

Collaborative mindset and enthusiasm for research excellence and continuous learning If you or anyone you know could be interested, please reach out to Fintan at TEC Partners for all of the details.

We're recruiting on behalf of a Cambridge-based AI research company developing data-efficient machine learning solutions for complex engineering and optimisation problems. This is an opportunity to join a highly research-driven ML lab, working on probabilistic modelling, Bayesian optimisation and decision-making methods, with a strong emphasis on theoretical rigour and real-world impact. The team regularly publishes at top-tier machine learning conferences and contributes to open-source ML libraries.