Staff Software Engineer, AI/ML

Google•Mountain View, CA

7h•$207,000 - $300,000

About The Position

Google software engineers develop technologies used by billions of people and work on projects critical to Google's needs. They are expected to bring ideas from a broad range of technical areas, demonstrate leadership, and take on problems across the full stack. The broader GenAI Data and Evaluation Platform team provides infrastructure and support to accelerate data and evaluation efforts across the Gemini program. In this role, you will coordinate across groups and accelerate work that brings serving impact to GDM Data and Evaluation efforts. At Google DeepMind, interdisciplinary teams advance AI to address complex global challenges and support product innovation, with safety and ethics as priorities. The role focuses on high-throughput serving infrastructure for evaluation workflows, scalable systems for massive evaluation datasets, efficient large-scale inference and evaluation pipelines, collaboration with research teams, and technical roadmaps for data-serving platforms. Individual pay is determined by job-related skills, experience, and relevant education or training. US compensation is $207,000–$300,000, plus a 20% bonus target, equity, and benefits.

Requirements

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 such as CPU, memory subsystem, and multiprocessing.
Experience designing software architecture for applications, including AI/ML systems.
Experience with site reliability engineering, system architecture, and distributed systems.
Experience building developer tools to improve development velocity, code quality, or code health, such as CI/CD, compilers, or test automation frameworks.

Nice To Haves

Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
8 years of experience with data structures and 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, such as Xbox or Capsules.
Understanding of the latest evaluation research and areas important to LLM research.

Responsibilities

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.