Senior Machine Learning Infrastructure Engineer, Simulation

Role Description

We seek an experienced Senior Machine Learning Infrastructure Engineer to lead the development of advanced AI/ML infrastructure for multi-billion parameter foundation models in ML accelerator-friendly simulations. Your expertise in massive model scaling, ML accelerators, and distributed training will be required for designing and scaling our systems.

This role reports to an Engineering Manager.

• Be part of a world-class, high-performing research engineering team to advance the state of the art of ultra realistic multi-agent simulations using foundation models.
• Collaborate closely with the core Google DeepMind and Waymo Realism Modeling teams in London, and Waymo Oxford to use the large models to improve sim realism.
• Provide deep technical leadership on large-scale ML model architectures, especially for autonomous vehicle models.
• Work at the intersection of data engineering, model development, and deployment, and provide guidance on architectural decisions and technical directions.
• Own large, complex systems, driving architectures that meet technical and business objectives.
• Design and scale large distributed systems covering the ML lifecycle, supporting planet-scale dataset generation and model training.
• Collaborate cross-functionally to derive performance and system-level requirements for large ML systems.
• Translate product/business goals into measurable technical deliverables, ensuring system component alignment.
• Mentor junior engineers, growing their expertise and fostering a collaborative culture.

Qualifications

• BS in Computer Science, Robotics, similar technical field of study, or equivalent practical experience.
• 5+ years of professional software engineering experience, with at least 3 years in machine learning infrastructure such as developing, scaling, training, deploying, and optimizing large-scale machine learning systems from data to model.

Requirements

• 10+ years of professional software engineering experience, with at least 5 years in machine learning infrastructure such as developing, designing, scaling, training, deploying, and optimizing large-scale machine learning systems from data to model.
• Solid experience in the development and optimization of machine learning infrastructure tools like DeepSpeed, PyTorch, TensorFlow, or similar frameworks.
• Strong expertise in distributed training techniques, including gradient sharding and optimization strategies for scaling large models across ML accelerator profiling tools to uncover performance bottlenecks.
• Deep understanding of state-of-the-art machine learning models such as auto-regressive transformers and familiarity with custom-kernels for diverse h/w compute based efficiency.
• Excellent communication skills, both verbal and written, with the ability to translate complex technical concepts for a broad audience.
• Practical familiarity in Autonomous Driving, Simulations, and ML accelerators is a plus.

Benefits

• Waymo employees are eligible to participate in Waymo’s discretionary annual bonus program.
• Equity incentive plan.
• Generous Company benefits program, subject to eligibility requirements.

Salary Range

The expected base salary range for this full-time position across US locations is $213,000 — $263,000 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level.