Applied Scientist / Machine Learning Engineer

Highlights

• Build embodied intelligence that moves real vehicles safely at scale.
• Turn petabyte-scale fleet data into training sets for AI Driver.
• Surface rare safety-critical scenarios to guide next model iteration.

What they offer

• Salaries benchmarked against the market annually
• Meaningful equity
• Relocation support
• Hybrid working and access to vehicle workshops and labs
• Learning and development support
• Comprehensive health, family, retirement and wellbeing benefits

Ideal candidate

ML-minded engineer who loves turning applied research into production and reasoning about data quality and coverage. Thrives in ambiguous, cross-functional work and is passionate about safe autonomy.

Requirements

• Strong machine-learning and software-engineering fundamentals with ability to take applied research into production
• Proficient in Python and a modern deep-learning framework and comfortable with SQL or large-scale data tools
• Experience with data curation, foundation models, large-scale data wrangling, computer vision, or model evaluation
• Can reason about sampling, class imbalance, label quality, dataset coverage, and experimental design
• Enjoy ambiguous, cross-functional problems and communicate technical trade-offs clearly