Senior Machine Learning Engineer - 3D

Harnham
London
1 week ago
Applications closed

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Candidates should take the time to read all the elements of this job advert carefully Please make your application promptly.Senior Machine Learning Engineer - 3D, london col-narrow-leftClient:Location: london, United KingdomJob Category: Other-EU work permit required: Yescol-narrow-rightJob Views: 3Posted: 05.05.2025Expiry Date: 19.06.2025col-wideJob Description:

Job Title: Machine Learning EngineerLocation:

London 1-2 days a weekVisa Sponsorship:

Is on offer for strong candidatesAbout the RoleMy client is hiring a

Machine Learning Engineer

to join a small but impactful team at the intersection of

deep learning, computer vision, and real-time 3D systems .This is a chance to push the boundaries of digital human performance, runtime tracking, and facial capture—projects that directly power high-end experiences.You’ll collaborate closely with a world-class VFX team, helping automate and optimize artist pipelines while building cutting-edge ML models that work with 3D data and real-world runtime systems.What You’ll Be Working OnDesigning and training deep learning models end-to-endExperimenting with GenAI architectures (VAEs, Diffusion Models, Transformers)Working with 3D geometry, meshes, and tools like BlenderSupporting automation efforts to streamline creative production pipelinesWhat We’re Looking ForSolid experience with deep learning and 3D modellingProficiency in C++ (especially for low-level or runtime systems)Familiarity with GenAI and recent ML research trendsExposure to 3D environments, animation, or game enginesComfort working in cross-disciplinary teams (engineering x creative)A portfolio of personal or open-source projects (GitHub is a plus)Nice to HaveEngineering background with a transition into ML/AIPrior work in gaming, VFX, graphics, or interactive mediaUnderstanding of facial capture, digital humans, and animation techInterview ProcessIntro Call (30 mins):

CV walkthrough + high-level tech screenTechnical Interview (1 hour):

Engineering, ML, and applied problem-solvingFinal Onsite (4–5 hours):

Meet the team, dive deeper, enjoy lunch

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