Senior Machine Learning Engineer, Simulation Evaluation

Waymo; San Francisco (CA); On-site; USD 213,000 - 263,000; Full time

Job summary

Waymo is seeking a Machine Learning Engineer to lead the evaluation of state-of-the-art simulation technologies aimed at enhancing the realism of autonomous driving systems. The ideal candidate will have a robust background in machine learning and experience deploying large-scale models.

Your responsibilities will include developing evaluation frameworks, mentoring engineers, and collaborating with research teams to integrate cutting-edge advancements. A salary range of $213,000 – $263,000 USD is provided for this role, reflecting the high level of expertise required.

Qualifications

• Five or more years of experience in machine-learning engineering or applied deep learning.
• Proficient programming skills in Python and hands-on experience with modern machine-learning frameworks.
• Experience designing and implementing evaluation frameworks for complex systems.

Responsibilities

• Lead the design and development of evaluation approaches for multimodal world models.
• Architect and implement machine-learning pipelines for realism evaluation.
• Collaborate with research teams to integrate advancements into production systems.

Skills

Machine Learning

Python

Deep Learning

Generative AI

Robotics

Education

Bachelor's, Master's, or PhD in computer science or related field

Tools

Jax

Flax

PyTorch

Job description

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver – the World's Most Experienced Driver – to improve access to mobility while saving thousands of lives lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. It has provided over ten million rider‑only trips, driven more than 100 million miles on public roads and tens of billions in simulation across 15 + U.S. states.

The Challenge

Waymo's simulator is one of the most complex virtual environments ever built. It blends deterministic logic, physical dynamics, and state‑of‑the‑art Generative AI to create a training ground for the Waymo Driver. The Simulator Evaluation team faces the ultimate data challenge: How do you mathematically prove that a virtual world is "real"?

Responsibilities

• Lead the design, development, and deployment of cutting‑edge evaluation approaches to assess realism of state‑of‑the‑art multimodal world models and generative systems for simulation use cases at Waymo.
• Architect and implement robust and scalable machine‑learning pipelines for tuning, evaluating, and deploying large‑scale discriminator models for the purposes of simulator realism evaluation.
• Evaluate open‑source and production‑ready video generation techniques that measure realism (e.g., temporal stability, multimodal consistency, geometric discrepancy, condition following).
• Apply vision‑language models to evaluate semantic understanding and controllability across our world simulation products.
• Collaborate with research teams across Waymo and Alphabet to integrate advancements in 4D world modeling and generative AI into production systems.
• Mentor engineers on the team and provide technical guidance on architecture and execution.

Qualifications

• Bachelor's, Master's, or PhD in computer science, machine learning, robotics, or a related field.
• Five or more years of experience in machine‑learning engineering or applied deep learning, supported by a portfolio of shipped products or peer‑reviewed publications.
• Proficient programming skills in Python and hands‑on experience with modern machine‑learning frameworks such as Jax, Flax, or PyTorch.
• Experience designing and implementing evaluation frameworks for complex systems or machine‑learning models.

Preferred Qualifications

• Track record of training large‑scale generative models (diffusion models, flow matching, vision‑language models, etc.).
• A PhD and demonstrated success delivering machine‑learning products focused on 3D generative models, world models, or video generation.
• Experience simulating sensor data, including camera, lidar, and radar, or modeling semantic scenes.
• Experience developing autonomous systems, robotics software, or autonomous vehicle simulations.
• Experience training and optimizing large‑scale models on GPU or TPU clusters for efficient production serving.
• Professional experience writing C++ for high‑performance production systems.

Salary Range: $213,000 – $263,000 USD