Principal Software Engineer, Autonomous Systems

1 week ago


Mountain View, Arkansas, United States Waymo Full time

Waymo is a pioneering company in autonomous driving technology, dedicated to becoming the most reliable driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has concentrated on creating the Waymo Driver—The World's Most Experienced Driver™—to enhance mobility access while preventing countless traffic-related fatalities. The Waymo Driver is the backbone of Waymo One, a fully autonomous ride-hailing service, and is adaptable to various vehicle platforms and applications. With over one million rider-only trips completed, the Waymo Driver has gained invaluable experience from driving autonomously across tens of millions of miles on public roads and billions in simulations across more than 13 U.S. states.

The Waymo ML Infrastructure team collaborates with both Research and Production teams to develop essential models in Perception and Planning, which are integral to our autonomous driving software. We provide our partners with optimal solutions throughout the entire model development lifecycle, crafted in close partnership with teams at Google. Our focus is on scaling models and addressing challenges unique to machine learning in the context of autonomous driving.

We create a suite of libraries and tools that enhance TensorFlow and JAX, tackling scalability, reliability, and performance issues faced by Waymo's machine learning practitioners. Our goals include: training efficiently at scale, optimizing ML accelerator performance, fine-tuning multimodal large language models for autonomous driving tasks, discovering hyper-parameters, re-training neural networks, and ensuring reliable metrics on validation sets, as well as validating newly trained deep neural networks when integrated into the complete onboard software stack.

In this hybrid role, you will report to an Engineering Manager.

Your Responsibilities:

  • Report to the Head of ML Training
  • Design distributed systems tailored for machine learning workloads of varying sizes, considering scalability, fault tolerance, and resource utilization
  • Enhance system performance by identifying bottlenecks and implementing effective algorithms for distributed training
  • Boost training efficiency across diverse neural network architectures
  • Refine the developer experience and performance of our scalable ML framework
  • Collaborate with machine learning engineers and other stakeholders to comprehend their needs and provide infrastructure support for their experiments and projects.
Your Qualifications:
  • Bachelor's degree in Computer Science, Mathematics, or 5+ years of equivalent practical experience
  • Industry experience in Python or C++
  • Previous exposure to Machine Learning frameworks (e.g., TensorFlow, PyTorch) and distributed training algorithms
  • Hands-on experience with ML accelerator profiling tools to identify performance bottlenecks
  • Understanding of ML compiler infrastructure, such as HLO and MLIR
  • Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and experience in deploying and managing distributed systems in cloud environments
Preferred Qualifications:
  • Master's degree in Computer Science or Mathematics
  • Prior experience in scaling model training across multiple accelerators
  • Experience with ML compiler optimization tools such as TVM or XLA
  • Knowledge of optimization techniques and deep learning algorithms
#LI-Hybrid

The expected base salary range for this full-time position across U.S. locations is outlined below. Actual starting pay will depend on job-related factors, including work location, experience, relevant training and education, and skill level. Your recruiter can provide more information about the specific salary range for the role location or, if the role is 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 comprehensive Company benefits program, subject to eligibility requirements.

Salary Range

$192,000 - $243,000 USD

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