Staff AI/ML Data & Model Infra Engineer

Google; United States; On-site; USD 207,000 - 300,000; Full time

Job summary

Google is hiring a Staff Software Engineer, Data and Model Insights and Infrastructure, in Mountain View, CA. You will shape the technical trajectory for complex ML systems, bridging research with production and influencing cross-functional teams.

You will lead design and deployment of scalable pipelines, mentor engineers, and collaborate with Product, Research, and UX to deliver production-ready AI solutions for Google Cloud.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience with one or more: Speech/audio, reinforcement learning, ML infrastructure, or related ML field.
• 5 years of experience with ML design and ML infrastructure (e.g., model deployment, evaluation, data processing, debugging, fine tuning).
• Experience integrating generative AI tools or LLM interfaces into workflows.

Responsibilities

• Lead the design and architecture of highly complex ML pipelines and distributed systems, ensuring scalability and reliability.
• Drive adoption of next-generation AI/ML techniques to solve high-impact problems and move prototypes to production.
• Set the gold standard for code quality, testing, and deployment within the team, and perform deep-dive architectural reviews.
• Mentor executive and mid-level engineers, fostering technical growth and cross-functional collaboration.
• Partner with researchers to operationalize models and align technical roadmaps with user needs.

Education

Bachelor's degree or equivalent practical experience

Master's degree or PhD in Engineering, Computer Science, or related field

Job description

Google is hiring a Staff Software Engineer, Data and Model Insights and Infrastructure, in Mountain View, CA. You will shape the technical trajectory for complex ML systems, bridging research with production and influencing cross-functional teams.

You will lead design and deployment of scalable pipelines, mentor engineers, and collaborate with Product, Research, and UX to deliver production-ready AI solutions for Google Cloud.