Senior Computer Vision & Face Recognition Engineer

Senior Machine Learning Engineer - Computer Vision & Face Recognition

Location: UK Remote / HybridLevel: Senior - 5+ years' production Computer Vision / ML experienceThe OpportunityAn exciting opportunity to take ownership of a production-grade facial recognition and Computer Vision platform, from model development through to deployment on NVIDIA edge hardware.This is not a research-only role.

You'll take models from development through to real-world deployment, working across face detection, alignment, embedding models, matching and evaluation, while balancing accuracy, performance and real-world constraints.You'll have genuine ownership of the face recognition capability and the opportunity to shape how the technology is built, evaluated and deployed.What You'll DoBuild and develop the full face recognition pipeline - detection, landmarks, alignment, quality filtering, embeddings and matching.Train, fine-tune and evaluate face embedding models, including decisions around training data and loss functions.Develop evaluation frameworks for 1:1 verification and 1:N identification, including FAR/FMR, FNMR, TAR and threshold selection.Build multi-camera Computer Vision pipelines for real-world deployment.Deploy and optimise models on NVIDIA edge GPUs, using ONNX, TensorRT and FP16/INT8 quantisation.Work with NVIDIA DeepStream to maximise real-time video processing performance.Design gallery and enrolment systems, including indexing, similarity search, template management and thresholding.Work closely with data protection and legal teams to build responsible biometric systems, including retention, auditability and privacy requirements.Benchmark and track model performance across releases.Review technical work and mentor mid-level engineers.What We're Looking For5+ years' production Computer Vision / Machine Learning experience.Proven experience building and deploying facial recognition systems using learned embeddings.Strong understanding of face detection, landmark alignment and embedding approaches such as ArcFace, CosFace or AdaFace.Strong understanding of 1:1 verification vs 1:N identification and biometric evaluation metrics.Strong Python, with C++ experience or willingness to work with it.PyTorch for training and ONNX/TensorRT for production deployment.Hands-on NVIDIA GPU, CUDA and inference optimisation experience.Docker, Linux, Git and CI/CD experience.Comfortable making technical decisions based on measurable accuracy and performance.Particularly Relevant ExperienceFacial recognition using CCTV or challenging real-world imagery, including low-resolution, off-angle faces, motion blur, occlusion and difficult lighting.NVIDIA DeepStream, GStreamer or Triton.Face quality assessment and template fusion.FAISS, HNSW or