Machine Learning Engineer, App SW

About the role

The Role
As an ML Engineer within the Application Engineering team, you’ll lead critical initiatives that push the frontier of model-based autonomous driving—both in terms of core driving performance and feature-level intelligence such as personalisation, comfort, and collaboration. You’ll design and deliver ML-driven behaviors that scale from assisted to autonomous driving. Your work will span across model architecture, data pipelines, evaluation frameworks, and real-world deployment. You’ll collaborate deeply with AI Platform, Simulation, Robot SW and Model Release teams to build systems that are performant, adaptable, and ready for production.

Responsibilities

• Develop and improve end-to-end driving models with state-of-the-art performance, robustness, and generalization.
• Lead projects on personalized and collaborative driving, including behavior conditioning, comfort tuning, and user alignment.
• Build evaluation pipelines and metrics for both closed-loop and open-loop driving performance and product readiness.
• Curate and mine real-world and synthetic data to drive scenario diversity, coverage, and feature-specific development.
• Influence architecture choices, training methodologies, and deployment pathways for production-scale learning systems.
• Collaborate cross-functionally across various teams to ensure integration and iteration velocity.
• Mentor senior engineers and shape the long-term technical direction across Autonomy.

Requirements

• Extensive and proven track record of shipping deep learning systems to production.
• Expert in deep learning (esp. sequential models, control, planning, or perception).
• Proficient in Python and other relevant languages (e.g. C++ and CUDA) and ML frameworks (esp. PyTorch), with a solid foundation in software engineering practices.
• Experience with real-time systems or robotics, ideally with simulation- or vehicle-in-the-loop components.
• Ability to lead technical initiatives across teams, drive alignment, and mentor engineers.

Desirable

• Prior work in autonomous driving, imitation learning, or trajectory prediction.
• Familiarity with personalization, human behavior modeling, or driver intent inference.
• Experience integrating ML systems into production hardware or multi-agent simulation.

Pay

Actual compensation is based on the candidate's skills, qualifications, and experience. The reasonably estimated salary for this role ranges from $283,500 to $381,600, plus a competitive equity package.

Schedule

This role is a full-time role based in Sunnyvale or Detroit (hybrid) and the reasonably estimated salary for this role ranges from $283,500 to $381,600, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience.