Lead Software Engineer, Infrastructure Quality, Robotics, DeepMind

Minimum qualifications:

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
• 8 years of experience programming in a general purpose coding language (e.g., C, C , Java, JavaScript, or Python).
• Experience in a people management, supervision/team leadership role.
  
  

Preferred qualifications:

• Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, or related technical fields.
• 3 years of experience in systems development engineering, system reliability engineering, software engineering with a focus on operations, or advanced systems administration.
  
  

About The Job

We believe there are many problems in the world in which robotics could play a significant role in making it easier, faster and safer for people to get things done. We’re looking for roboticists, designers, hardware and software engineers to help us explore these possibilities, develop breakthrough technologies, and build new products that could help millions of people.

This is a dedicated Software Quality and Engineering Productivity leadership role. In this role, you will be an expert whose primary passion and career focus is building, owning, and scaling the quality of software releases and AI model validation on standard and custom hardware. You will play a major role in influencing the velocity at which our team solves AGI in the physical world. As our software and hardware infrastructure grows to support the increasing scale of robotics research, we need to continuously build and upscale our testing, reliability, validation, release strategy, and overall engineering productivity and velocity.

Robotics infrastructure is uniquely difficult. You will be solving for non-deterministic hardware wear-and-tear, complex large-scale model deployment, fast inference, and the massive data requirements of AGI. You will be experienced with software quality and release strategy on custom or experimental hardware. Your work will directly determine how many iterations our engineers and scientists can run per day, week, and year, while holding a high quality bar.

Artificial intelligence will be one of humanity’s most transformative inventions. At 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 learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

The US base salary range for this full-time position is $262,000-$365,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .

Responsibilities

• 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.
  
  
  

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .