Senior/Staff Machine Learning Engineer, Infrastructure Senior Software Engineer, Simulator Platform Senior Software Engineer, Planner Senior Software Engineer, ML Data Infrastructure Senior Machine Learning Engineer, Robotics (AI)

Location: Onsite in Mountain View, California or San Francisco, California

Salary: $251,000–$310,000 USD annual base salary, plus eligibility for an annual bonus, equity incentive plan, and company benefits.

Company

Waymo develops autonomous driving technology and operates a fully autonomous ride-hail service powered by the Waymo Driver.

What you will do

• Design, build, and optimize realistic multi-agent simulation environments and business logic running on TPUs with JAX and TensorFlow.
• Implement model-parallel and data-parallel strategies for training and running foundation models on TPU hardware.
• Integrate foundation models into simulation pipelines in collaboration with modeling teams.
• Lead technical architecture and system design across data engineering, simulation execution, and performance optimization.
• Profile ML accelerator systems, identify bottlenecks, and improve end-to-end execution speed.
• Translate product and business objectives into technical requirements and system deliverables.

Requirements

• 6+ years of professional software engineering experience, including at least 4 years focused on machine learning infrastructure.
• Hands-on ML programming experience on TPU and GPU hardware with JAX, PyTorch, or TensorFlow.
• Experience scaling large models through model parallelism, data parallelism, or distributed training.
• Strong knowledge of modern ML models, including autoregressive transformers, and ML accelerator profiling tools.
• Ability to independently lead ambiguous technical initiatives and build robust libraries, pipelines, and developer tooling.
• Strong verbal and written communication skills for collaboration across distributed, cross-functional teams.

Nice to have

• Experience with reinforcement learning, Sim2Real transfer, or robotics.
• Experience with distributed ML frameworks and GPU/TPU accelerators.
• Familiarity with autonomous driving systems, multi-agent simulations, or realistic world modeling.

Culture & Benefits

• Work at the intersection of ML infrastructure, foundation models, and simulation engineering.
• Collaborate across distributed, cross-functional engineering and modeling teams.
• Eligibility for a discretionary annual bonus program and equity incentive plan.
• Company benefits are available subject to eligibility requirements.