Software Engineer, Robotics, Infrastructure Quality and Productivity, DeepMind

Responsibilities

• Implement and support testing environments across the full robotics stack. This includes building automated software harnesses for large-scale model training, serving, evaluation, and Hardware-in-the-Loop (HIL) systems for conventional and on-robot testing.
• Build and manage robust CI/CD pipelines, staging environments, and release workflows. Implement regression checks validating correctness, throughput, and stability across evolving machine learning models, software services, and physical robot hardware.
• Monitor engineering productivity metrics and build tooling to eliminate bottlenecks and reduce friction across teams. Maintain code health and optimize the ML flywheel, from data ingestion to model training and physical robot deployment.
• Collaborate with senior engineers to identify and integrate automation and AI tooling across our ecosystem, from streamlining root-cause analysis to generating synthetic edge-case scenarios for testing.
• - Implement and support testing environments across the full robotics stack. This includes building automated software harnesses for large-scale model training, serving, evaluation, and Hardware-in-the-Loop (HIL) systems for conventional and on-robot testing. - Build and manage robust CI/CD pipelines, staging environments, and release workflows. Implement regression checks validating correctness, throughput, and stability across evolving machine learning models, software services, and physical robot hardware. - Monitor engineering productivity metrics and build tooling to eliminate bottlenecks and reduce friction across teams. Maintain code health and optimize the ML flywheel, from data ingestion to model training and physical robot deployment. - Collaborate with senior engineers to identify and integrate automation and AI tooling across our ecosystem, from streamlining root-cause analysis to generating synthetic edge-case scenarios for testing.

Minimum qualifications: