Machine Learning Engineer

Machine Learning Engineer Overview

This is an opportunity to join a well-supported deep tech startup as an early machine learning hire, working on applied computer vision problems that have not yet been solved in a straightforward way. The team is intentionally small and highly experienced, with people who have come from respected research groups, major technology companies, and leading universities. The company is looking for someone who wants to help shape the technical direction of the work from an early stage and who is motivated by difficult, real-world engineering challenges.

What the role involves

• Building machine learning and computer vision systems that can perform well outside of controlled benchmark settings.
• Creating models that cope with noisy inputs, limited labelled data, and highly variable operating conditions.
• Improving how the team uses data so that useful models can be trained from very small datasets and sparse supervision.
• Working on methods that generalise across different domains, rather than only succeeding on one narrow dataset.
• Designing inference solutions that are accurate and efficient enough to run on lightweight edge devices instead of depending on large cloud infrastructure.
• Developing custom pipelines to process raw, messy, real-world data into a form suitable for training and evaluation.
• Taking responsibility for projects from initial idea through implementation and delivery, with a high level of technical ownership.
• Contributing to an early-stage technical team where your work will help define the product and engineering approach.

What they are looking for

• Strong hands-on experience with PyTorch and good habits around clean, maintainable deep learning engineering.
• Confidence working with modern model architectures, including transformers and vision-language models, as well as newer approaches where appropriate.
• A solid foundation in classical computer vision and signal processing principles.
• Evidence that you can own technical projects end to end rather than only working on isolated modelling tasks.
• Comfort building data pipelines from imperfect, real-world source data.
• Experience with efficient deployment or inference on edge hardware is a significant advantage.
• An interest in tackling hard technical problems in a startup setting where you will have real responsibility and room to build.
• Ability to work in person from the London office, as this is an early-stage, office-based team.

What is on offer

• A highly desirable salary package.
• The chance to join a quickly scaling startup at an early point in its journey.
• Work on challenging applied computer vision problems with real-world impact.
• Exposure to a senior, technically strong team with backgrounds spanning research, industry, and academia.
• Substantial ownership and the opportunity to help create something new rather than maintain an existing system.
• In-person collaboration in London with a team that values serious technical work.

How to apply

If this sounds like the right next step, you can apply now or get in touch with the recruiter contact named on the page for a conversation about the role.

Degree Requirement: Not Specified

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