Senior ML Systems Architect — Production & Data

Google LLC; Mountain View (CA); On-site; USD 262,000 - 364,000; Full time

Job summary

Google LLC is seeking a senior software engineer with extensive ML design and leadership experience to drive end-to-end AI/ML deployments at scale. You will work on complex ML pipelines and distributed systems, setting standards for code quality, testing, and production readiness.

You will mentor engineers, collaborate with researchers, and coordinate with product teams to align technical roadmaps with user needs, while contributing to Google Cloud AI initiatives and scalable infrastructure.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 7 years of experience leading technical project strategy, ML design and optimizing end-to-end ML.
• 5 years of experience with one or more of: speech/audio, RL, ML infrastructure, or another ML field.
• 5 years of experience with design and architecture; testing/launching software products.

Responsibilities

• Understand the design and architecture of highly complex ML pipelines and distributed systems.
• Drive the adoption of next-generation AI/ML techniques to production.
• Set the "gold standard" for code quality, testing, and deployment within the team.
• Mentor engineers and represent the team in high-level technical discussions.
• Partner with researchers to operationalize models and align roadmaps with user needs.

Skills

Software development

Technical leadership

ML design

End-to-end ML deployment

Education

Bachelor's degree or equivalent practical experience

Master’s or PhD in Engineering/CS

Job description

Google LLC is seeking a senior software engineer with extensive ML design and leadership experience to drive end-to-end AI/ML deployments at scale. You will work on complex ML pipelines and distributed systems, setting standards for code quality, testing, and production readiness.

You will mentor engineers, collaborate with researchers, and coordinate with product teams to align technical roadmaps with user needs, while contributing to Google Cloud AI initiatives and scalable infrastructure.