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Augur Initiative Ltd

Real-time security intelligence from sensor networks

Machine Learning Researcher

AI ResearchConfirmed live in the last 24 hours
Full-timeLondon, UKNo salary listed

About the Job

Requirements

  • A PhD, or a Master's with equivalent research experience, in Computer Vision, Machine Learning, or a related discipline.
  • A strong publication record at leading journals or conferences is considered a plus.
  • 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.
  • Strong Python and PyTorch skills, including the ability to write testable, production-quality code and participate actively in code reviews.
  • Ability to formulate research problems independently, define technical direction, and communicate findings clearly in writing and discussion.

Responsibilities

  • 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.
  • Formulate problems, design experiments, and drive research from prototype through to production-grade systems for real-time spatial intelligence.
  • Help shape the research roadmap, mentor junior researchers and interns, and strengthen the organisation's presence in the research community.
  • Work on-site at least two days weekly, including one Thursday.

Desired Qualifications

  • Published work at leading journals or conferences.

About the Company

Augur Initiative Ltd

Real-time security intelligence from sensor networks

Augur builds a resilience technology platform that turns dispersed sensor data into real-time intelligence for national security and public safety. Its AI perception engine plugs into existing cameras and sensors to detect unusual behavior, connect activities across locations, and reconstruct incident timelines without facial recognition, using anonymized movement patterns. It differentiates itself through privacy-by-design, reliance on anonymized signals rather than facial data, seamless integration with legacy hardware, and a software‑as‑a‑service delivery that avoids expensive upgrades. Its goal is to strengthen the resilience of public spaces and critical infrastructure by providing timely, privacy-conscious situational awareness to governments, infrastructure operators, and large venues so threats can be detected early and responses coordinated.

Company size
11-50
Company stage
Early VC
Total funding
$15M
Headquarters
London, United Kingdom
Founded
2024

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