About Augur
Augur transforms legacy sensor systems into real-time operational intelligence. We help organisations act before threats escalate – not after damage is done. Everything we build is privacy-first by design.
Our platform connects to existing cameras and sensors to detect threats, retrace events, and surface real-time insights – all without replacing a single device. Augur helps teams reduce risk, cut costs, and grow revenue through better visibility, faster decisions, and fewer blind spots.
Our culture is built on a foundation of radical candor and mutual trust. We recognise that being an industry leader requires more than just building exceptional products – it requires empowering a team of exceptional people. Individually, we operate with high autonomy; collectively, we’re unified by a shared drive to achieve our mission through a commitment to excellence.
We are looking for an ML Researcher to join our Machine Learning team in London.
This role sits at the intersection of cutting-edge research and mission-critical deployment. You will own research directions end-to-end, developing novel algorithms at the intersection of computer vision, deep learning, metric learning, 3D geometry, and vision-language modelling.
You will formulate problems, design experiments, and drive your work from prototype through to production-grade systems that power real-time spatial intelligence across complex environments. We aim to publish at top venues and deploy at scale, and we're looking for researchers who want to do both.
The role includes opportunities to shape Augur's research roadmap, mentor junior researchers and interns, and strengthen our presence in the research community. Work on-site at least two days weekly, specifically one day being a Thursday.
Key Skills
Academic Track Record: PhD (or Master's with equivalent research experience) in Computer Vision, Machine Learning, or a related discipline. Published work at leading journals or conferences is considered a strong plus.
Core CV & Spatial AI: Deep expertise in areas such as metric learning, multi-view geometry, depth estimation, 3D scene understanding, rendering techniques, feature-based tracking, self-supervised learning, or learning-based mapping and localisation.
Engineering Rigor: Strong Python and PyTorch skills; ability to write testable, production-quality code and participate actively in code reviews.
Autonomy: Capable of independently formulating research problems, defining technical direction, and communicating findings clearly in both writing and discussion.
Accessibility and inclusivity
At Augur, our culture is built on radical candor and mutual trust. To solve the complex, physical-world problems our customers face, we need a team that thinks differently.
Whether you’re self-taught, have a non-traditional background, or are returning to the workforce, if you have the grit and the experience we’re looking for at Augur, we’d love to hear from you.
We are committed to fostering a diverse workplace and ensuring an accessible hiring experience - please let us know if you require any accommodations during the interview process to help you do your best work.
Skills Required
- PhD in Computer Vision, Machine Learning, or related discipline; or Master's with equivalent research experience
- Published research at leading journals or conferences
- Deep expertise in metric learning, multi-view geometry, depth estimation, 3D scene understanding, rendering techniques, feature-based tracking, self-supervised learning, mapping and localisation, or vision-language modelling
- Strong Python and PyTorch skills and ability to write testable, production-quality code
- Experience driving research from prototype to production-grade, real-time deployed systems
- Ability to independently formulate research problems, define technical direction, and communicate findings clearly
- Ability or willingness to mentor junior researchers and interns
- Work on-site at least two days weekly, including Thursday
What We Do
Augur Initiative Ltd is a sensor technology company that transforms legacy sensor systems into real-time operational intelligence. It provides sensor fusion and machine learning solutions for security applications, enabling organizations to detect threats and surface real-time insights through a privacy-first platform that connects to existing cameras and sensors without requiring device replacement.
