Staff Software Engineer, AI/ML

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

• Lead the architectural design of high-throughput serving infrastructure for evaluation workflows.
• Design scalable systems to store, process, and serve massive datasets for model evaluation.
• Optimize the latency and resource efficiency of large-scale inference and evaluation pipelines.
• Collaborate with research teams to define infrastructure requirements for next-generation AI models.
• Establish technical roadmaps for data serving platforms supporting DeepMind's evaluation ecosystem.

Minimum qualifications:

• Experience designing, building, and operating large-scale distributed systems, with a focus on scalability, fault tolerance, and reliability.
• Experience in Machine Learning or AI infrastructure.
• Experience in software performance analysis and improvement, and High-Performance computer architectures (e.g., CPU, memory subsystem, multiprocessing).
• Experience designing software architecture for applications, including AI/ML systems.
• Experience with site reliability engineering, system archiecture, and distributed systems.
• Experience building developer tools to improve development velocity, code quality, or code health (e.g., CI/CD, compilers, test automation frameworks).

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  
• 8 years of experience with data structures/algorithms, with strong proficiency in C++ or Python.
• Experience developing and optimizing ML or production serving infrastructure.
• Experience leading complex architectural migrations or cross-team infrastructure projects. Excellent problem-solving skills and ability to collaborate widely across organizations.
• Knowledge of VMs and sandboxed execution environments (e.g., Xbox, Capsules).
• Understanding of the latest evaluation research and areas important to LLM research.