Staff Machine Learning Engineer, Waymo

• B.S. in Computer Science, Math, or equivalent real-world experience
• 7+ years building and maintaining high-scale distributed or ML inference systems
• Coding and testing skills, specifically Python/C++
• Familiarity with large-scale fleet management, testing, and deployment, e.g.: GCP/AWS/Kubernetes, Jenkins, GCS/S3, etc
• Familiarity with large-scale MLOps tools, e.g.: tf.serving/Torchserve, Kubeflow/Sagemaker Pipelines/Vertex AI Pipelines, etc
• Understanding of machine learning fundamentals and experience with popular ML frameworks such as JAX, PyTorch, or TensorFlow

Desirable

• The Predictive Planning team (PrePlan) develops and deploys state-of-the-art machine learning solutions that predict the future state of the world and plan the Waymo Driver’s behavior
• Our mission is to transform Waymo's unprecedented scale of driving data into robust, generalizable, and performant deep neural networks
• These models enable the autonomous vehicle to navigate complex environments safely and efficiently
• The team’s work touches on all of the most exciting aspects of machine learning, including but not limited to Large Language Models (LLMs), Reinforcement Learnings (RL), and Vision understanding
• In this role, you will ensure that our systems remain reliable in the face of this rapid, experiment-driven development
• In this hybrid role, you will report to a Technical Lead Manager
• Collaborate with data scientists, engineers, and other stakeholders to deploy machine learning models into production
• Develop and maintain CI/CD pipelines for automating data generation, model training, testing, and deployment processes
• 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, Beam etc)