We're looking for ML engineers to accelerate development progress and improve our ML developer experience. Ideally, you've worked in a fast-paced development environment before. We're looking for software engineers who love making both the teams they work with and the GPUs they work with more productive. In this role you will design, build, and maintain the tools to track our whole model development lifecycle - such as feature store, experiment tracking, and model registry. This will also include: Implement tools to track the model development lifecycle for an efficient deployment and evaluation process. Develop issue detection and alerting mechanisms for critical ML services (training jobs, data pipelines, model deployments) to quickly detect issues and ensure high uptime. Maintain observability dashboards to track model performance, data quality, and system metrics. Champion best practices for robust, reproducible, and debuggable ML experimentation. Collaborate with cross-functional teams (perception, behavior, mapping, simulation teams, etc.) to identify infrastructure needs and integrate solutions across various domains for end-to-end ML solutions. Thoughtfully balance innovative exploration with practical considerations.