Senior Software Engineer, ML Evaluation (Infrastructure)

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.

You will:

• Collaborate with Machine Learning Engineers, Data Scientists, and ML Infrastructure Engineers to surface signals on model, component, and system performance
• Develop, scale, and maintain CI/CD pipelines for automating metric computation, aggregation, and monitoring
• Build data management tooling to improve reproducibility and scale analyses automatically as Waymo drives more miles
• Collaborate with ML and product teams to define evaluation criteria and translate those into metrics and targets
• Stay current with emerging technologies and trends in ML evaluation and metrics design.
• Be aware of best practices used in the Alphabet stack of ML technologies (e.g. TF, JAX, Flax, Beam etc).

You have:

• B.S. or higher in Computer Science, Math, or equivalent real-world experience
• 4+ 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 ML 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.

We prefer:

• Experience developing and maintaining evaluation pipelines for ML models
• Experience deploying and supporting machine learning models for computer vision, natural language processing, robotics/motion planning, or recommendation systems.
• Experience supporting a large team of MLEs developing high-capacity, production-grade models and components
• Strong understanding of metrics computation and regression detection at scale