This job is closed
We regret to inform you that the job you were interested in has been closed. Although this specific position is no longer available, we encourage you to continue exploring other opportunities on our job board.
ML Engineer, Perception Foundation Model
Waymo - San Francisco, CA
posted 16 days ago
About the position
Waymo is an autonomous driving technology company with the mission to be the 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 One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states. The mission of the Waymo Applied Research team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of the 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. In this hybrid role, you will report to a Research Director.
Responsibilities
- Lead the effort of model-platform co-optimization for Waymo's perception foundation model
- Dive deep to training and inference efficiency on various platforms such as TPU, GPU, and CPU
- Collaborate with other teams, such as perception, simulation, and ML infrastructure, to drive the model optimization
- Be curious, innovative, and productive
Requirements
- 2+ years of experience with designing or optimizing neural networks using Transformers and ConvNets
- Experience on optimizing model efficiency for either large-scale training or inference
- Able to learn new models and new frameworks
- Experience optimizing ML models
Nice-to-haves
- Experience with low-level optimizations, on CPU/GPU/TPU
- Experience with designing or evaluating or optimizing Transformers
Benefits
- Discretionary annual bonus program
- Equity incentive plan
- Generous Company benefits program
