Staff ML Engineer (Perception)

TL;DR

Staff ML Engineer (Perception): Developing and deploying multimodal foundation models and world models for 3D perception in autonomous driving using camera, LiDAR, and radar data, with an accent on scalable training, inference optimization, and evaluation. Focus on designing distributed model-training systems, building large-scale distillation and data pipelines, and improving model efficiency through sharding, quantization, pruning, and knowledge distillation.

Location: Hybrid work schedule in the United States, with listed locations in Mountain View, San Francisco, New York City, and Kirkland.

Salary: $251,000–$310,000 USD base salary, plus potential annual bonus, equity, and company benefits.

Company

Waymo develops autonomous driving technology and fully autonomous ride-hailing services through the Waymo Driver.

What you will do

• Train and deploy multimodal large language models and world models for 3D perception using camera, LiDAR, and radar data.
• Collaborate with research and engineering teams to deploy models and establish continuous training workflows.
• Optimize Transformer training and inference with quantization, pruning, knowledge distillation, efficient attention, partitioning, and sharding.
• Build scalable training, evaluation, distillation, and bulk-inference data pipelines.
• Design evaluation frameworks and performance-analysis tools for perception models.
• Profile and debug large-scale machine learning systems and infrastructure.

Requirements

• Master’s or PhD in Computer Science, Machine Learning, Robotics, or a related technical field.
• 4+ years of industry or postdoctoral research experience in reinforcement learning or foundation models.
• Experience implementing scalable and distributed training workflows, including data parallelism, FSDP, and other sharding approaches.
• Proficiency in JAX and Flax, with potential experience in TensorFlow or PyTorch.
• Experience optimizing Transformer training and inference and working with globally distributed inference infrastructure.
• Ability to work in the United States under the stated hybrid work arrangement.

Nice to have

• PhD-level research in reinforcement learning, foundation models, or multimodal learning.
• Contributions to high-impact industry AI projects.
• Experience with generative models for world models, images, video, or 3D, including diffusion or autoregressive methods.
• Contributions to frameworks that improve training speed and scalability, such as JAX, Gemax, or XManager.

Culture & Benefits

• Health, dental, vision, life, and disability insurance.
• 401(k) with company match, paid vacation, sick time, and 13 paid holidays per year.
• Maternity leave and baby bonding leave.
• Eligibility for an annual discretionary bonus, equity incentive plan, and company benefits program.
• Work focused on safe autonomous driving, large-scale machine learning, and collaboration across research and engineering teams.