2 months ago
Base Salary
$349k - $431k/yr
Responsibilities
- Advance post-training techniques for AI running onboard autonomous vehicles.
- Develop and lead the strategy for a next-generation post-training system built on existing large-scale models.
- Keep current with post-training research and identify applications for autonomous driving problems.
- Participate in the leadership community advancing Waymo’s machine learning stack.
- Partner with ML platform teams to build effective and scalable post-training capabilities.
- Guide teams in adopting effective post-training strategies based on their needs.
- Influence engineering strategy while balancing day-to-day technical leadership.
Requirements
- Master’s degree in computer science emphasizing machine learning or an equivalent degree; PhD preferred.
- 10+ years of leadership experience in a large-scale machine-learned production system.
- Experience leading a production post-training system used by more than 100 million users while solving multiple targeted problems in parallel.
- Experience building metrics, data, and flywheels for post-training applications.
- Experience influencing without authority at the director and VP level or higher.
- Ability to balance hands-on leadership with developing and influencing engineering strategy.
Benefits
- Hybrid work schedule.
- Eligibility for a discretionary annual bonus program, equity incentive plan, and company benefits program, subject to eligibility requirements.
- Full-time position with salary varying by work location and job-related factors.
Categories
AI ResearchML Engineering
About Waymo
Waymo develops the Waymo Driver, a full-stack autonomous driving system, and operates the Waymo One robotaxi service that offers paid, driverless rides in select U.S. cities. The company monetizes through ride-hailing fares and partnerships integrating its technology on multiple vehicle platforms. Founded in 2009 as Google’s self-driving project, Waymo is headquartered in Mountain View and is an Alphabet subsidiary, with over 10 million rider-only trips and 100+ million autonomous miles on public roads.