Staff ML Engineer, Search AI Infrastructure

Google LLC; Mountain View (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google LLC in Mountain View, CA, is seeking a Staff ML Software Engineer for the Search Ecosystem to build scalable ML systems and infrastructure that power AI-driven content and search experiences. You will work on model training, evaluation, deployment, and serving, with emphasis on integrating generative AI into workflows and ensuring robust, secure platforms.

You will lead technical initiatives across teams, influence architecture decisions, and mentor engineers while delivering high-impact

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of software development experience, including 5 years testing and launching software products, and 3 years in design/architecture.
• 5 years building ML systems and infrastructure (training, evaluation, deployment, serving).
• Experience integrating generative AI tools or LLM interfaces into workflows.
• Experience in data processing software (Hadoop, Spark, Beam, Hive) and related strategies/algorithms.

Responsibilities

• Develop and implement frameworks to evaluate AI system components and data quality.
• Analyze results to drive improvements in system performance and value models.
• Lead high-level technical strategy for your area of ownership.
• Leverage LLM knowledge to design, build, and maintain specialized infrastructure on top of LLMs.
• Drive projects from ideation to production in a fast-paced environment.

Skills

Software development

ML systems design

Generative AI integration

Data processing concepts

Education

Bachelor’s degree or equivalent practical experience

Master’s degree or PhD in Engineering or CS

Tools

Hadoop

Spark

Beam

Hive

ETL/ELT

MapReduce

Flume

Job description

Google LLC in Mountain View, CA, is seeking a Staff ML Software Engineer for the Search Ecosystem to build scalable ML systems and infrastructure that power AI-driven content and search experiences. You will work on model training, evaluation, deployment, and serving, with emphasis on integrating generative AI into workflows and ensuring robust, secure platforms.

You will lead technical initiatives across teams, influence architecture decisions, and mentor engineers while delivering high-impact