Computer Vision Research Engineer

My client is a fast-growing technology business doing genuinely impactful work, building platforms that make physical environments safer and more intelligent. They operate at the cutting edge of computer vision and real-time AI, and they are scaling quickly.

The team is high-calibre, operates with autonomy and has a culture built on trust and candour. This is a business where the work matters and the people are given the space to do it well.

The Role

They are looking to bring on an ML Researcher to join the machine learning team in London. You will own research directions end-to-end, from problem formulation through to production deployment, working across a range of computer vision and deep learning disciplines.

The expectation is to publish at top venues and ship at scale. There is also real scope to shape the research roadmap and mentor junior researchers as the team grows.

Requirements

• PhD, or Master’s with equivalent research experience, in Computer Vision, Machine Learning or a related discipline
• Published work at leading conferences or journals is a strong plus
• Deep expertise across one or more computer vision or spatial AI research areas
• Strong Python and PyTorch skills, with the ability to write production-quality code
• Able to work independently, define technical direction and communicate findings clearly

What’s in it for you?

• Hard problems with real-world impact
• Publish at top venues and deploy at scale
• High autonomy and direct influence over the research roadmap

• PhD, or Master’s with equivalent research experience, in Computer Vision, Machine Learning or a related discipline
• Published work at leading conferences or journals is a strong plus
• Deep expertise across one or more computer vision or spatial AI research areas
• Strong Python and PyTorch skills, with the ability to write production-quality code
• Able to work independently, define technical direction and communicate findings clearly, * Hard problems with real-world impact
• Publish at top venues and deploy at scale
• High autonomy and direct influence over the research roadmap