Senior Engineering Manager - Scalable Machine Learning

Role overview A senior engineering manager is needed to lead the Scalable Machine Learning team within an autonomous driving organization developing hands-free driver assistance technology. The team builds the data generation, orchestration, and distributed training infrastructure that powers machine learning across the company, sitting at the intersection of ML Platform, Jobs Platform, Cloud Platform, and High Performance Computing. The role combines hands-on people leadership with cross-organizational technical strategy, acting as the bridge between adjacent platform groups without direct authority over them.

Responsibilities - Lead and mentor a team of software engineers working on large-scale ML infrastructure, driving high technical standards. - Define and own the multi-quarter technical strategy for data generation, orchestration, and distributed training. - Represent the team in organization-level planning and architecture decisions, resolving cross-team tradeoffs on shared infrastructure such as GPU scheduling, job orchestration, storage, and compute cost. - Drive advanced MLOps practices, including model artifact management, experiment tracking, and automated deployment and testing. - Build durable technical partnerships with peer managers and architects on adjacent platform teams. - Hold the team and its systems to a high reliability bar, including how cross-team incidents are root-caused, fixed, and prevented.

Requirements - Bachelor's degree with 10+ years or Master's degree with 8+ years in Computer Engineering, Computer Science, Electrical Engineering, Robotics, or a related field. - At least 10 years of software development experience, including 5+ years in a Staff, Principal, or senior technical leadership role. - Track record of setting technical strategy across multiple teams or organizations, not just within a single team. - Extensive experience designing and operating large-scale distributed systems and cloud infrastructure for machine learning, including shared compute concerns like GPU scheduling, quota, job orchestration, and multi-tenant clusters. - Strong proficiency in Python for production-quality, high-performance software. - Demonstrated ability to influence and align peer teams and leaders without direct authority.

Nice to have - Master's or PhD in Computer Science, Electrical Engineering, Robotics, or a related field. - Hands-on experience with distributed ML frameworks such as Ray, PyTorch, Dagster, LakeFS, or PyArrow. - Multi-sensor data fusion experience relevant to autonomous driving. - Familiarity with safety-critical software development in automotive or robotics domains. - Deep understanding of ML concepts, computer vision, and L2/L3 autonomy challenges.

Benefits and work setup - Competitive compensation with annual bonus programs, equity, and a generous benefits package. - Medical, dental, and vision insurance for individuals and families, plus an HSA with employer match. - Employer-matched 401(k) with immediate vesting, employer-paid group term life insurance, and voluntary life coverage. - Paid parental leave, adoption and surrogacy support, and paid medical leave. - Unlimited vacation plus 15 paid holidays, with daily lunches and snacks available in office locations. - Pre-tax healthcare, dependent care, and commuter spending accounts; monthly wellness stipend. - Backup child and elder care, professional development reimbursement, and an employee assistance program. - Legal, identity theft, and pet insurance discounts, employee resource groups, and a quarterly team activity stipend. - Expected base salary range in California: $253,120 – $379,680 USD, depending on location, experience, and skills. - US-based candidates only; visa sponsorship is available.