Staff ML Infra Engineer — Scale Production ML (Equity)

Waymo LLC; San Francisco (CA); On-site; USD 251,000 - 310,000; Full time

Benefits offered by this job

Discretionary annual bonus

Equity incentive plan

Generous benefits program

Job summary

Waymo LLC in the United States is recruiting a senior ML engineer to design and operate ML infrastructure for the DUE team. You will bring models from data to production, scale training and inference, and ensure reliability across real-world and simulation data.

You will collaborate with cross-functional teams, mentor engineers, and help set the technical direction for scalable ML systems using Python and C++, with JAX, TensorFlow, or PyTorch. A strong ML systems background is essential.

Qualifications

• BS in CS, ML, or related field, or equivalent practical experience.
• 7+ years building ML systems.
• Experience designing, scaling, training, deploying, and optimizing large-scale ML systems.
• Strong Python and/or C++ coding.
• Experience with JAX, TensorFlow, or PyTorch.
• Ability to set technical direction and influence partner teams.

Responsibilities

• Lead the design and development of ML infrastructure for DUE models from data to training to production serving.
• Design and scale distributed systems for large-scale dataset generation, model training, and evaluation.
• Own reliability, efficiency, and observability of production ML serving.
• Keep offline evaluation and production inference consistent.
• Mentor engineers and drive technical direction across teams.
• Collaborate with modeling, evaluation, and platform teams to translate product goals into technical deliverables.

Skills

Python

C++

ML Systems

Distributed Systems

Education

BS in Computer Science / Machine Learning or related field

MS/PhD preferred

Tools

JAX

TensorFlow

PyTorch

Job description

Waymo LLC in the United States is recruiting a senior ML engineer to design and operate ML infrastructure for the DUE team. You will bring models from data to production, scale training and inference, and ensure reliability across real-world and simulation data.

You will collaborate with cross-functional teams, mentor engineers, and help set the technical direction for scalable ML systems using Python and C++, with JAX, TensorFlow, or PyTorch. A strong ML systems background is essential.