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.

In this role, you'll:

• Report to the Model Training and Inference Reliability TLM
• Design and implement scalable, reliable, and efficient ML infrastructure and pipelines.
• Collaborate with data scientists, engineers, and other partners to deploy machine learning models into production.
• Develop CI/CD pipelines for automating data generation, model training, testing, and deployment processes.
• Monitor and optimize model performance, scalability, and reliability in production environments.
• Implement best practices for model versioning, monitoring, and governance.
• Troubleshoot and resolve issues related to model deployment and performance.
• Stay current with emerging technologies and trends in ML Ops and DevOps domains.
• Be aware of best practices used in the Alphabet stack of ML technologies (e.g. TF, JAX, Flax, or Beam).

At a minimum, we'd like you to have:

• B.S. in Computer Science or Math, or equivalent real-world experience
• 5+ years building and maintaining high-scale distributed or ML inference systems
• Code and testing skills, specifically Python/C++
• Familiarity with large-scale fleet management, testing, and deployment (e.g. GCP/AWS/Kubernetes, Jenkins, GCS/S3)

It's preferred if you have:

• Previous experience deploying and supporting machine learning models for computer vision, natural language processing, or recommendation systems
• Understanding of machine learning fundamentals and experience with popular ML frameworks such as JAX, PyTorch, or Tensorflow

#LI-Hybrid

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.