Machine Learning Engineer London

Augur Initiative Ltd; Greater London; On-site; GBP 80,000 - 110,000; Full time

Job summary

Augur Initiative Ltd is seeking an ML Engineer to advance state-of-the-art scene understanding, object detection, tracking, and 3D reconstruction from edge-deployed sensors. You will evaluate research, build efficient inference pipelines, and partner with product and backend teams to deploy production-grade CV models.

Ideal candidates combine deep technical depth with a practical mindset, capable of leading architectural decisions, and mentoring others as Augur scales its real-time intelligence

Qualifications

• Solid understanding of modern computer vision techniques including object detection, tracking and depth estimation.
• Experience deploying CV models to production environments; ONNX/TensorRT familiarity is a plus.
• Comfort navigating academic literature and benchmarking SOTA models for production integration.

Responsibilities

• Lead architectural decisions for CV capability development and deployment in a fast-moving team.
• Collaborate with product and backend teams to deploy production-grade CV models at scale.
• Mentor teammates and shape the future of CV capabilities at Augur.

Skills

Core ML/CV

Deployment

Research Fluency

Engineering Rigor

Autonomy

Tools

PyTorch

Torchvision

OpenCV

Lightning

W&B

Job description

Augur transforms legacy sensor systems into real-time operational intelligence. We help organisations act before threats escalates - 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.

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.