Machine Learning Engineer, Training

4 weeks ago


Mountain View, Arkansas, United States Waymo Full time

At Waymo, we're working towards a future where autonomous driving technology improves access to mobility while saving thousands of lives. Our mission is to be the most trusted driver, and we're looking for talented engineers to help us achieve this goal.

The Waymo ML Infrastructure team is responsible for developing models in Perception and Planning that are core to our autonomous driving software. We work closely with Research and Production teams to ensure our partners receive the best solutions for the entire model development lifecycle.

We're seeking a skilled Machine Learning Engineer to join our team and contribute to the development of our distributed training infrastructure. In this role, you will be responsible for developing the infrastructure components necessary for distributed training, including job scheduling, resource management, data distribution, and model synchronization.

Key responsibilities include:

  • Developing automation solutions for provisioning, deployment, monitoring, and scaling of distributed training infrastructure
  • Monitoring system health, diagnosing and troubleshooting issues, and performing routine maintenance tasks
  • Identifying performance bottlenecks and optimization opportunities
  • Improving the developer experience and performance of our scalable ML framework

Requirements include:

  • Bachelor's degree in Computer Science, Engineering, or related field, or 2+ years equivalent experience
  • Experience with distributed systems principles and experience building distributed systems for production environments
  • Solid Python or C++ skills
  • Prior experience with Machine Learning frameworks (e.g., TensorFlow, PyTorch) and distributed training algorithms

We prefer candidates with practical familiarity using ML accelerator profiling tools to uncover performance bottlenecks, familiarity with cloud computing platforms (e.g., AWS, Azure, GCP), and knowledge of optimization and deep learning algorithms.



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