Machine Learning Researcher

You will be responsible for exploring solutions to interesting problems in a variety of domains, using techniques including language models, neural networks, statistical methods, and classical machine learning where appropriate. You will work both as an independent researcher and in team collaborations. You will also be responsible for implementing your machine learning models in the wider software stack. As we deploy our machine learning models in a variety of settings, including on edge devices, you will be expected to produce optimised solutions for both latency and memory.

Please note this is a hybrid role, with a compulsory attendance of 2 days a week in the Cambridge office.

We are looking for a curious and motivated machine learning professional with a strong academic or industry background in AI, machine learning, or a related field. You will be comfortable applying machine learning techniques to solve complex real-world problems, working collaboratively within a multidisciplinary team, and communicating technical concepts to a range of stakeholders. A proactive approach to learning, problem-solving, and innovation will be key to success in this role.

Essential:

Candidates must have a PhD or master's degree in machine learning or a related discipline or equivalent experience.

Experience with Python machine learning libraries (e.g. PyTorch, TensorFlow, scikit-learn)

Experience with a variety of machine learning techniques.

Be a team player but with the ability to operate autonomously and take independent decisions.

Desirable:

Familiarity with Linux and Git

Basic understanding of cybersecurity concepts and common threats