AI Research Engineer - 3D Computer Vision

You will be part of a computer vision team specialising in scene understanding and localisation, responsible for building systems for scene matching, geo-registration, simultaneous localisation and mapping (SLAM), and 3D reconstruction. You will develop and extend state-of-the-art architectures and pipelines, design rigorous experiments, and conduct benchmarks to evaluate and improve real-world performance, including adaptation to the compute constraints and operational requirements of downstream deployments.

What you'll do

• Develop and benchmark scene matching and geo-registration pipelines robust to challenging conditions such as changes in illumination, viewpoint, season, or sensor modality.
• Build and evaluate SLAM, visual odometry, or structure-from-motion systems for deployable platforms under real-world operational constraints.
• Research and adapt state-of-the-art geometric deep learning or feature matching methods to concrete use cases, from local feature descriptors to learned place recognition.
• Collaborate with product and downstream deployment teams to integrate localisation and reconstruction outputs into navigation or decision-making pipelines and shape the roadmap for new capabilities.
• Apply and develop techniques to adapt models to target hardware and constraints associated with downstream ML/AI tasks.

What you'll need

• MSc in computer science, machine learning, robotics, or a closely related field, with experience in designing, implementing, and thoroughly evaluating advanced AI-based systems.
• Hands-on experience developing localisation, scene matching, or 3D reconstruction systems, with understanding of what it takes to make these systems reliable under real-world data distributions and deployment constraints.
• Deep familiarity with modern approaches to geometric computer vision and deep learning, including learned feature matching, place recognition, visual SLAM, visual-inertial odometry (VIO), or neural 3D representations such as neural radiance fields (NeRF).
• Solid software engineering skills, writing clean and well-structured code in Python, with experience deploying AI software to production including testing, QA, and monitoring.
• Excellent communication skills and ability to report and present research findings clearly and efficiently, both internally and externally.

Nice to have

• PhD in computer vision, machine learning, robotics, or a related field, with publications in top-tier venues (e.g. CVPR, NeurIPS, ICLR, ICCV, ICRA, IROS, ECCV).
• Experience designing, evaluating, and delivering end-to-end AI systems on edge devices with constrained compute resources.
• Experience with simulators, emulators, or synthetic data generation pipelines for geometry or localisation tasks.
• Experience with Rust and/or C++.

What they offer

• Direct contribution to the protection of democratic countries while balancing ethical and geopolitical concerns.
• Work on unique technical challenges with highly unusual requirements and constraints where robustness, safety, and ethical considerations are vital.
• Opportunity to work with world-leading experts in geometric computer vision, deep learning, and AI systems.
• Responsible autonomy and critical thinking encouraged, with focus on outcomes and impact.