Join Hudl’s Hardware Group as a Senior MLOps Engineer to design and operate scalable edge infrastructure that deploys neural networks to thousands of devices, own the model compilation pipeline (including TensorRT, FP16/INT8, calibration, and validation), implement automation and telemetry for production models, solve edge constraints (low-bandwidth updates, storage limits, network failures), and mentor teammates on Python tooling, IaC, and CI/CD. Location preference is near London or Barcelona; remote candidates in the UK and Spain are also considered.

Join the Athlete Performance group to develop large-scale systems that combine live video and biomechanical data streams, solving real-time synchronization and ML inference challenges for coaches and medical teams. Work as part of a cross-functional product team to deliver full-stack web features, mentor other engineers, and iterate frequently. Preferred tech experience includes C#/Node, React, TypeScript, MongoDB/SQL/Elasticsearch and AWS. Location: applicants within commuting distance of London; hybrid with expectation of more in-office days, though remote UK candidates are considered.