You will:
- Conduct comprehensive experimentation to train and deploy state-of-the-art Multimodal LLMs and World models to perform 3D Perception using sensor information from Camera, LiDAR and Radar..
- Partner effectively with engineering and research teams across Waymo to deploy new models, and implement efficient workflows for model development and continuous training on new front-filled data.
- Apply and develop techniques such as quantization, pruning, knowledge distillation, and efficient attention mechanisms.
- Develop and maintain scalable data pipelines for Training & Eval to process data from multiple sources.
- Design and implement evaluation frameworks for perception models.
- Develop infrastructure for large-scale model distillation and bulk-inference pipelines for teacher models.
- Experiment with different model partitioning and sharding strategies to improve scalability and efficiency.
- Build and maintain tools for performance analysis, profiling (e.g., xprof), and debugging of ML models.
You have:- PhD or Masters in Computer Science, Machine Learning, Robotics, or a similar technical field, with 4+ years of industry or post-doc research experience in Reinforcement Learning or Foundation Models.
- Proficiency in implementing model training flows in a scalable, distributed and performant manner such as Data parallel, FSDP and other sharding approaches.
- Proficiency in JAX, Flax, and potentially TensorFlow/PyTorch.
- A willingness to work with complexity of globally distributed inference infrastructure.
- Hands on experience with optimizing the training and inference of Transformer architectures
We prefer:- PhD in Computer Science, Machine Learning, or Robotics, with a research focus on Reinforcement Learning, Foundation Models, or Multi-Modal learning.
- Substantial involvement in and contributions to high impact industry AI projects.
- Experience in generative models for domains such as world models, images, videos, 3D, using techniques such as diffusion or autoregressive models.
- Experience contributing to frameworks and libraries that improve training speed and scalability (e.g., JAX, Gemax, XManager)
Disclosure for WA Based & Remote Roles:In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
Health, dental, vision, life, disability insurance Retirement Benefits: 401(k) with company match Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary) Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks Baby Bonding Leave: 18 weeks Holidays: 13 paid days per year
The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.
Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
Salary Range
$251,000-$310,000 USD
