Machine Learning Engineer, Application Software

The Application Software team pushes the frontier of model-based autonomous driving, improving core driving performance and developing intelligent features such as personalisation, comfort and collaboration. The role covers designing and delivering ML-driven behaviours that scale from assisted to autonomous driving, spanning model architecture, data pipelines, evaluation frameworks and real-world deployment. The role works closely with AI Platform, Simulation, Robot Software and Model Release teams. This is a full-time role based in Sunnyvale, CA, or Detroit, MI, with a hybrid working model.

Responsibilities

Develop and improve end-to-end driving models, advancing their performance, robustness and generalisation; Lead technical initiatives in personalised and collaborative driving, including behaviour conditioning, comfort tuning and alignment with user preferences; Build evaluation pipelines and metrics to assess open-loop and closed-loop driving performance and product readiness; Curate and mine real-world and synthetic data to improve scenario diversity, coverage and feature-specific development; Collaborate across engineering teams to integrate models, accelerate iteration and support real-world deployment; Mentor senior engineers, drive technical alignment and influence architecture, training and deployment decisions

Requirements

Extensive, proven track record of shipping deep learning systems to production; Deep expertise in deep learning, particularly sequential models, control, planning or perception; Proficient in Python, experienced with relevant languages such as C++ or CUDA, and confident using ML frameworks, especially PyTorch; Strong foundation in software engineering practices and experience building reliable, maintainable ML systems; Worked with real-time systems or robotics, ideally including simulation-in-the-loop or vehicle-in-the-loop components; Can lead technical initiatives across teams, build alignment and mentor engineers

Nice to have

Experience in autonomous driving, imitation learning or trajectory prediction; Familiarity with personalisation, human behaviour modelling or driver intent inference; Experience integrating ML systems into production hardware or multi-agent simulation

Benefits

Salaries benchmarked against the market annually; Meaningful equity; Relocation support and visa sponsorship where applicable; Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs; Learning and development budgets with support for training, conferences and growth; Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more