Principal Machine Learning Engineer

### Who you are
- 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
- 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
- We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply

### What the job involves
- As a Principal 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 personalization, comfort, and collaboration
- You’ll design and deliver ML-driven behaviours 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
- 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

### Benefits
- Private healthcare: Choose our optional health insurance for comprehensive coverage for you and your family.
- Paid time off: Paid vacation plus public holidays and additional leave programs, ensuring you have time to unwind.
- Mental health resources: Through Spill, you can access therapy and mental health support.
- Community and socials: Join clubs or attend team socials to connect over hobbies, sports, or just for fun.
- Competitive compensation: Our compensation package includes cash and equity, making you a true partner in our success.
- Learning and development: Budgets for books, courses, and company-wide training to support your continuous growth.