Machine Learning Engineer, Perception and Sensor Simulation Job at Waymo, California

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  • Waymo
  • California

Job Description

Waymo is an autonomous driving technology company with the mission to be the 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 now lost to traffic crashes. The Waymo Driver powers Waymo One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states.

The Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing and training the Waymo Driver. Your team will be a diverse, and collaborative group of machine learning (ML) engineers, software engineers and data scientists. We develop industry-leading simulation solutions using advanced ML algorithms that measure and enhance the performance of the Waymo Driver. We achieve those goals by jointly modeling the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists), roads, traffic control systems, and weather conditions, and the full sensor suite including camera, Lidar and radars.

To increase the fidelity, scalability and controllability of our simulations,we employ the latest ML technologies such as large language models, foundational world models, and reconstructive methods trained on large-scale datasets with both generative and reconstructive technologies.

In this hybrid role, you will report to a Senior Staff Engineering Manager

You Will

  • Join our world-class research engineering team and drive innovation in ultra-realistic sensor data and perception simulation for autonomous vehicles. You will develop the latest simulation technologies using foundation models for embodied agents.
  • Apply your deep ML expertise, in Generative AI (GenAI), to push the boundaries of simulation realism and directly influence the advancement of autonomous driving technology.
  • Work in close collaboration with Waymo's foundational AI research team to transfer State-of-The-Art research into scalable and production-ready solutions.

You Have

  • PhD in Computer Science, Machine Learning (ML), Robotics, or similar technical field of study, or equivalent practical experience.
  • 2+ years of experience with ML engineering and applied Deep Learning.
  • 2+ years of experience on Multi-modal Generative Models, including diffusion or foundational world models, OR machine learning-based 3D Reconstruction techniques, including 3D Gaussian Splatting (3DGS) and Neural Radiance Fields (NeRF), depth estimation techniques.
  • Fluency in Python, with experience developing ML software using frameworks such as PyTorch, TensorFlow and Jax/Flax

We Prefer

  • Experience with processing or simulating (Lidar, Camera, or MIMO Radar) sensor data.
  • Experience with autonomous systems including robotics or autonomous vehicles (L4, L3+).
  • Experienced with C++, in integrating ML models into a production system.
  • Experience training large-scale models on GPU/TPU clusters.

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.

Salary Range

$170,000—$216,000 USD

Job Tags

Full time, Remote job,

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