Staff Machine Learning Engineer – VLM/LLM Evaluation
Waymo · Mountain View, CA | San Francisco, CA | Kirkland, WA | New York City, NY · AI Foundations (7SJ)
About this role
Waymo is hiring a staff-level Machine Learning Engineer based in Mountain View, CA | San Francisco, CA | Kirkland, WA | New York City, NY (hybrid). The posting calls out experience with Python, C, TensorFlow, PyTorch and roughly 5+ years of relevant work. Listed education preference: a master's degree or equivalent. Compensation is listed at $238,000–$302,000 per year.
- Role
- Machine Learning Engineer
- Function
- machine learning
- Level
- staff
- Track
- Tech leadership
- Employment
- Full-time
- Location
- Mountain View, CA | San Francisco, CA | Kirkland, WA | New York City, NY
- Work mode
- Hybrid
- Experience
- 5+ years
- Education
- Master's degree
- Department
- AI Foundations (7SJ)
More roles at Waymo
Job description
from Waymo careersWaymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.
This role follows a hybrid work schedule and you will report to a Senior Staff Software Engineer.