Software Engineer, Robotics, Infrastructure Quality and Productivity, DeepMind

At Google DeepMind our mission is to build the world's first general-purpose learning agent. Central to this mission is the complex task of measuring the intelligence of our prototypes. As a Software Engineer, you will be working with the cutting edge AI agents developed by our exceptional team of Machine Learning and Neuroscience research scientists. Your responsibilities will include everything from creating systems for agent testing using 2D and 3D games to developing test problems within physics simulators. You will create graphical visualization of results, build competitive agent leaderboards and test new algorithms on robots. To succeed in this role you will need to have a strong foundation in software engineering and enjoy working on a wide range of challenging problems within a mission-driven team.

Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

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:

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.