AI/ML Software Engineering Manager, Home Conversations

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

Benefits offered by this job

Bonus target 20%

Equity

Benefits

Job summary

Google is seeking an Software Engineering Manager for AI/ML in the Google Home Conversational Experiences team in Mountain View, CA. You will lead engineering across Gemini for Home, shaping the conversational platform and guiding multiple teams in hybrid AI architectures.

You will drive technical direction, collaborate with research and product teams, and focus on end-to-end performance, latency, and reliability in a fast-paced, evolving environment.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years leading ML design and optimizing ML infrastructure.
• 5 years with one or more ML areas: speech/audio, RL, ML infra, or related field.
• 3 years in a technical leadership role.
• 2 years in people management or team leadership.

Responsibilities

• Drive the technical architecture and roadmap for the conversational experiences platform powering Gemini for Home.
• Architect and deploy hybrid AI systems to maximize quality, safety, and reliability.
• Diagnose production gaps, reduce latency, and resolve complex issues across pipelines.
• Partner with researchers, product managers, and data scientists to evaluate algorithms and data infra.
• Lead and grow an engineering team, guiding career development and performance.

Skills

Outcome ownership

Stakeholder influence

Problem solving

English proficiency

Education

Bachelor's degree

Master's or PhD preferred

Tools

ML infrastructure

NLP frameworks

Job description

Google is seeking an Software Engineering Manager for AI/ML in the Google Home Conversational Experiences team in Mountain View, CA. You will lead engineering across Gemini for Home, shaping the conversational platform and guiding multiple teams in hybrid AI architectures.

You will drive technical direction, collaborate with research and product teams, and focus on end-to-end performance, latency, and reliability in a fast-paced, evolving environment.