Software Engineering Manager, AI/ML, Google Home Conversational Experiences

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

Software Engineering Manager, AI/ML, Google Home Conversational Experiences

Location: Mountain View, CA, USA

Experience Level: Advanced

Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain.

Notice: In most instances, this position requires in-person interviews as part of the hiring process.

Minimum Qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine-tuning).
• 5 years of experience with one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• 3 years of experience in a technical leadership role.
• 2 years of experience in a people management or team leadership role.

Preferred Qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
• Applied research expertise with LLMs, preferably for NLP purposes.
• Ability to effectively operate with flexibility in a fast-paced, constantly evolving team environment.
• Excellent written and verbal communication skills in English.

About the Job

Like Google’s own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs.

As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started — and as a manager, you guide the way.

With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.

We are the Conversational Experiences team that powers the Gemini-based dialog engine for Gemini for Home, bringing improvements and new capabilities to how users can talk to and get things done with Google Home devices and app.

In this role, you will maintain and improve the conversational platform powering Gemini for Home. You will combine generative AI solutions with classic deterministic architectures to raise conversational quality and drive down end-to-end latency.

The Google Home team focuses on hardware, software and services offerings for the home, ranging from thermostats to smart displays. The Home team researches, designs, and develops new technologies and hardware to make users’ homes more helpful. Our mission is the helpful home: to create a home that cares for the people inside it and the world around it. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US Salary: $207,000 – $300,000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Drive the technical architecture and roadmap for the conversational experiences platform powering Gemini for Home across task-oriented and open-domain dialogue systems.
• Architect and deploy hybrid AI systems combining generative large language models with deterministic components to maximize conversational quality, safety, and operational reliability.
• Diagnose production quality gaps, reduce end-to-end system latency, and resolve complex issues across context ingestion, multimodal inputs, memory, and dialogue execution pipelines.
• Partner cross-functionally with research scientists, product managers, and data scientists to evaluate algorithms, design scalable data infrastructure, and launch user-facing features.
• Lead and grow an engineering team, setting clear technical direction, guiding individual career development, and fostering a high-performance culture.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google’s Applicant and Candidate Privacy Policy.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google’s EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.

If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.

Locations: Mountain View, CA, USA

Experience Level: Advanced

Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain.