Google's Chrome browser aims to become smarter, personalized, and proactive. The Chrome Intelligence Infrastructure team is responsible for building the Machine Learning infrastructure and capabilities, including Generative AI and non-Generative AI, to achieve this strategy. This involves enabling Chrome feature teams to quickly integrate intelligence into their solutions, impacting billions of users through on-device ML model delivery, inference, server-side services, and data pipelines.
Requirements
- Experience in designing, building, and maintaining distributed systems or back-end infrastructure.
- Experience with Machine Learning concepts, tools, and frameworks (e.g., TensorFlow, TFLite).
- Experience with ML infrastructure, such as model serving platforms, data pipelines, or ML operations.
- Experience contributing to codebases like Chromium.
- Experience in ML performance, large-scale systems data analysis, ML debugging, LLMs, or specialized areas within ML.
- Knowledge of on-device ML deployment and optimization techniques.
- Experience with software design and architecture.
Responsibilities
- Design, build, maintain, and optimize scalable and reliable ML infrastructure for on-device and server-side Chrome features, including systems for model management, serving, execution, performance, and monitoring across Google3 (e.g., Go, C++, Java) and Chromium (C++).
- Collaborate with Chrome feature teams to understand requirements, provide guidance, and integrate ML solutions into the Chrome browser.
- Lead the technical design and implementation of complex, multi-quarter projects, making well-reasoned technical decisions to address ambiguous problems.
- Contribute to code health, system maintainability, and documentation.
- Build and support the infrastructure and services that enable Chrome feature teams to quickly incorporate intelligence into their solutions.
- Develop on-device ML model delivery and inference, server-side metadata and GenAI services, and data pipelines.
- Work on the latest technologies to deliver agentic solutions to users.
Other
- Mentor other engineers on the team, fostering their technical growth.
- Lead the technical design and implementation of complex, multi-quarter projects, making well-reasoned technical decisions to address ambiguous problems.
- Experience leading the design and execution of significant technical projects.
- Versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack.
- Bachelor’s degree or equivalent practical experience.
