Senior Engineer - Computer Vision / Machine Learning

<h3><strong>(Internal Only) Senior Engineer - Computer Vision / Machine Learning</strong></h3><p style="min-height:1.5em"> <strong>Location:</strong> UK (London) preferred, Hungary considered<br /> <strong>Contract:</strong> Permanent full-time<br /> <strong>Level:</strong> 4</p><h3><br /><strong>About the Role</strong></h3><p style="min-height:1.5em">You'll own the CV and physical-modelling layer within DemTech's tracking pipeline - working on top of ML-provided detection models to produce trajectory and positional outputs (e.g. trajectory estimation, motion reconstruction, 2D-to-3D reconstruction problems).</p><p style="min-height:1.5em">This role exists because tracking data is only as useful as the reconstruction layer that sits between detection and the outputs people actually rely on - dashboards, officiating decisions, performance insight. You'll own that layer within a small, fast-moving sports technology product team, working with real-world data.</p><p style="min-height:1.5em">You'll also be expected to work within DemTech's AI-first ways of working - using AI-delegated and AI-augmented development practices as a normal part of how you build, not as a separate initiative layered on top.</p><p style="min-height:1.5em"><br /><strong>Key Responsibilities</strong></p><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Own the day-to-day delivery of the 2D-to-3D reconstruction pipeline - converting raw detections into positional and trajectory outputs using physics-based modelling (trajectory estimation, motion reconstruction, projectile physics), operating with autonomy within agreed direction.</p></li><li><p style="min-height:1.5em">Work directly with the ML discipline team on model performance - proposing and prototyping improvements where applied CV work surfaces opportunities, rather than only consuming their output. Strong performers here are expected to shape R&amp;D-adjacent proposals, not just execute them.</p></li><li><p style="min-height:1.5em">Hold a genuine voice in technical decisions on algorithm design and data pipeline structure - contribute to architectural milestones and offer insight on peers' work, including alternative solutions and design tradeoffs.</p></li><li><p style="min-height:1.5em">Own the accuracy and reliability of tracking outputs across variable, real-world deployment conditions.</p></li><li><p style="min-height:1.5em">Support optimisation and deployment of models onto embedded, resource-constrained hardware, using deployment techniques such as TensorRT, ONNX, quantisation, pruning, and bottleneck profiling.</p></li><li><p style="min-height:1.5em">Use AI-delegated and AI-augmented development practices as a standard part of the role.</p></li></ul><p style="min-height:1.5em"><strong>Key Attributes &amp; Skills</strong></p><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Strong applied computer vision experience, with solid grounding in mathematical and physical modelling - trajectory estimation, motion reconstruction, projectile physics, or comparable 2D-to-3D reconstruction problems.</p></li><li><p style="min-height:1.5em">C++ required; Python experience is a plus for prototyping and tooling.</p></li><li><p style="min-height:1.5em">Working knowledge of ML techniques, with genuine interest in contributing to model improvement conversations and proposing R&amp;D-adjacent ideas - core training and validation sit elsewhere.</p></li><li><p style="min-height:1.5em">Practical experience with model deployment and optimisation tooling (e.g. TensorRT, ONNX, quantisation, pruning, bottleneck profiling) for embedded or resource-constrained environments.</p></li><li><p style="min-height:1.5em">Experience with camera-based data sources, tracking pipelines, or spatial/temporal data.</p></li><li><p style="min-height:1.5em">Comfortable with ambiguity - this is a build-phase product with evolving scope.</p></li><li><p style="min-height:1.5em">Strong communication skills - able to work with data platform, backend, and frontend engineers on data contracts and outputs, and to explain complex problems and solutions clearly to others.</p></li></ul><p style="min-height:1.5em"><strong>What This Role Is Not</strong></p><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Not a primary ML research role - core model training and validation sit with the ML discipline team or associated ML engineers, though close collaboration and proposing improvements is expected.</p></li><li><p style="min-height:1.5em">Not a data engineering role - a separate role owns storage, transformation, and API exposure of the outputs produced here.</p></li><li><p style="min-height:1.5em">Not a people-management role by default - this is an individual contributor position with genuine technical ownership of the CV/reconstruction domain, day-to-day and under agreed direction rather than final sign-off authority.</p></li></ul><div style="min-height:1.2em;margin-top:0;margin-bottom:0"> </div><div style="min-height:1.2em;margin-top:0;margin-bottom:0"> </div><div style="min-height:1.2em;margin-top:0;margin-bottom:0"> </div><div style="min-height:1.2em;margin-top:0;margin-bottom:0"> </div><div style="min-height:1.2em;margin-top:0;margin-bottom:0"> </div><div style="min-height:1.2em;margin-top:0;margin-bottom:0"> </div><p>Find more <a href="https://www.arbeitnow.co.uk/english-speaking-jobs">English Speaking Jobs in United Kingdom</a> on Arbeitnow</a>