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Augur

Machine Learning Engineer

London
Posted 1 day ago
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Location: London

Department: Machine Learning

Team: Machine Learning

Posted: 15 July 2026

Position type: Full-time Hybrid

Apply on: Ashby

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.

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I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

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Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

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Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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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.

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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.

Apply on: Ashby

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Skills

Machine Learning
Computer Vision
Object Detection
Tracking
3D Reconstruction
Python
PyTorch
Torchvision
OpenCV
ML Tooling
SLAM
Depth Estimation
Benchmarking
Autonomy
Inference Pipelines
Research Fluency

Location

London, England, United Kingdom

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