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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer, Robotics, Infrastructure Quality and Productivity, DeepMind - **Company:** Google - **Location:** London, UK - **Contract:** Permanent contract - **Skills:** C++ (Programming Language), Software Quality, Continuous Integration, DevOps, Hardware-In-The-Loop Simulation, Python (Programming Language), Linux System Administration, Machine Learning, Smart Devices, Software Engineering, Graphics Processing Unit (GPU), Data Ingestion, Delivery Pipeline, Information Technology, Machine Learning Operations - **Published:** September 17, 2026 - **Apply:** https://dejobs.org/x/x/B09A52B196BD4752B69873C45D1E70F1/job/ ## About the Role * Bachelor's degree in Computer Science, Robotics, or equivalent practical experience. * 2 years of experience in software engineering, DevOps, CI/CD infrastructure, or engineering productivity. * 2 years of experience building and maintaining automated testing frameworks and release pipelines. * 2 years of C++ and Python programming experience. * 1 year of experience with large-scale model training, serving, and evaluation systems or production ML workflows. * 1 year of experience in embedded systems or Hardware-in-the-Loop (HIL) testing. Preferred qualifications: * Industry experience in robotics or automation systems. * Experience maintaining build, release, and deployment systems across heterogeneous architectures (e.g., TPUs, GPUs, edge devices) and custom Linux environments. * Experience with advanced AI tooling and automation specifically focused on engineering productivity and software quality. * Team player, willing to learn from and with others, and work closely with research, hardware, and operations colleagues. * Comfortable working with a geographically distributed team in a fast-changing environment. ## Description * 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. ## Related Videos - [Shifting Stress to Progress— Understanding DevOps to do DevOps Better](https://www.wearedevelopers.com/videos/268-shifting-stress-to-progress-understanding-devops-to-do-devops-better) - [Agent Smith Gets Hardware: Autonomous IoT Hacking From Debug Port to Cloud API](https://www.wearedevelopers.com/videos/100258-agent-smith-gets-hardware-autonomous-iot-hacking-from-debug-port-to-cloud-api) - [When React Meets Reality: Building a Real-Time Control Room for Autonomous Vehicles](https://www.wearedevelopers.com/videos/2091-when-react-meets-reality-building-a-real-time-control-room-for-autonomous-vehicles) - [Robots are coming into the wild! 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