Job Description

Join a mission-focused technology consultancy delivering breakthrough AI and machine learning solutions to complex, real-world problems. You will apply your curiosity, creativity, and rigour to design and deploy ML systems across diverse projects, working in multi-disciplinary teams of highly skilled scientists and engineers.
In this role, you will:

• Research, design, and build ML models, pipelines, and systems, often in novel or resource-constrained environments.
• Rapidly prototype and test feasibility while moving concepts toward client-ready demonstrators and deployable products.
• Solve problems across the entire ML development cycle: ideation, data preparation, model development and refinement, and packaging for deployment.
• Collaborate across engineering and scientific domains to explore pioneering technologies and deliver impactful solutions.

What they're looking for:

• A 2:1 or above in a relevant discipline (Physics, Maths, Engineering, Computer Science, or similar). Advanced degrees or equivalent R&D experience are highly valued.
• Strong Python programming skills.
• Hands-on experience with frameworks such as TensorFlow, PyTorch, or JAX.
• Experience designing ML solutions in novel problem spaces or constrained environments (e.g., edge processing).
• Familiarity with a broad range of ML techniques (computer vision, generative models, audio processing, etc.), or the ability to adapt quickly to new areas.
• Exposure to GPU programming (e.g., CUDA) is a plus.
• Ability to communicate complex technical ideas clearly to colleagues and stakeholders.

Client-facing experience or a willingness to engage with stakeholders and project teams is highly desirable.
Why join?

• Work on projects that have meaningful real-world impact.
• Contribute ideas in a flat, collaborative environment that values openness and innovation.
• Access well-equipped labs and modern offices with on-site amenities.
• Benefit from clear opportunities for growth into project leadership or client-facing roles, supported by experienced peers.