Design, implement, and own the long-term roadmap and execution for large scale software and HWITL testing environments, conventional and on-robot testing, as well as manual and automated.
Design, deploy, and manage a robust software release discipline, with flexible powerful staging environments, and comprehensive regression checks for software, AI models, and robot hardware over time.
Define productivity metrics such as code in prod, bottlenecks, code debt, reducing, and improving code health, and optimize the Data/ML Flywheel, from ingestion and labeling to model evaluation and deployment.
Lead application of agentic AI, including automating root-cause analysis of HWITL failures, edge-case scenarios, or data quality or AI model performance problems.
Drive end-to-end system reliability for software systems and robot fleets. Partner with external hardware vendors and internal teams to co-develop, integrate, and test joint software and hardware releases.

Lead Software Engineer, Infrastructure Quality, Robotics, DeepMind

Job Description