Machine Learning Engineer

Augur

Greater London

On-site

GBP 75,000 - 110,000

Full time

14 days+

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Job summary

Augur is seeking an ML Engineer to join our growing technical team in the UK. This role focuses on developing advanced computer vision capabilities for edge-deployed sensors, including scene understanding, object detection, tracking, and 3D reconstruction.

You will evaluate state-of-the-art research, build efficient inference pipelines, and collaborate with product and backend teams to deploy production-grade CV models while maintaining an autonomy-driven, fast-moving environment.

Qualifications

  • Solid understanding of modern CV techniques (object detection, tracking, depth estimation, 3D geometry, SLAM).
  • Strong Python skills; experience with PyTorch, Torchvision, OpenCV, and ML tooling (Lightning, W&B).
  • Familiarity with deploying CV models to production and evaluating state-of-the-art research.

Responsibilities

  • Develop advanced CV capabilities for edge-deployed sensors.
  • Build efficient inference pipelines and production-grade models.
  • Collaborate with product and backend teams to deploy CV capabilities.

Skills

Core ML/CV
Deployment Focus
Research Fluency
Engineering Rigor
Autonomy

Tools

PyTorch
Torchvision
OpenCV
Lightning
Weights & Biases (W&B)

Job description

About Augur

Augur transforms legacy sensor systems into real-time operational intelligence. We help organisations act before threats escape – 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 Engineer to join our growing technical team. This role is critical in developing advanced capabilities in scene understanding, object detection, tracking, and 3D reconstruction from edge-deployed sensors.

You will play a key part in evaluating and integrating state-of-the‑art research, building efficient inference pipelines, and collaborating closely with product and backend teams to deploy production‑grade CV models.

We’re looking for someone with strong technical depth, a practical mindset, and a drive to tackle hard problems at the intersection of research and real‑world product. The role includes opportunities to lead, mentor, and shape the future of our CV capabilities.

Key Skills
  • Core ML/CV: Solid understanding of modern CV techniques (e.g. object detection, tracking, depth estimation, 3D geometry, SLAM).

  • Deployment Focus: Strong background in deploying CV models to production; familiarity with ONNX/TensorRT a plus.

  • Research Fluency: Comfortable navigating academic literature, benchmarking SOTA models, and integrating them into product pipelines.

  • Engineering Rigor: Strong Python skills; experience with PyTorch, Torchvision, OpenCV, and ML tooling (e.g. Lightning, W&B).

  • Autonomy: Capable of defining technical direction, leading architectural decisions, and working independently in a fast‑moving environment.

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.

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