Senior Machine Learning Infrastructure Engineer, Simulation

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.

You have:

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.

We prefer:

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.

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.