Software Engineering Manager, Generative AI, Google Conversational

Software Engineering Manager, Generative AI, Google Home Conversational Experiences

Share Software Engineering Manager, Generative AI, Google Home Conversational Experiences

Google Mountain View, CA, USA

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

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

• 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).
• 3 years of experience in a technical leadership role.
• 2 years of experience with GenAI techniques (e.g., Large Language Models (LLMs), Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
• 2 years of experience in a people management or team leadership role.

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 3 years of experience working in a complex, matrixed organization.
• Applied research expertise with LLMs 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.

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile;

the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

With your extensive technical expertise you take initiative to independently design and implement new systems, designing, implementing, and testing multiple features with little or no direction from tech lead or manager. You collaborate with key stakeholders to determine future direction of work.

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

We are looking for a technically manager to evolve the Gemini for Home conversational stack and experiment/productize bleeding-edge generative-AI solutions (e.g., natural language understanding, response generation, multi-modal inputs, execution, and context/memory ingestion).

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: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google .

• Design and productize scalable generative AI architectures to significantly improve natural language understanding, multi-modal inputs, and context ingestion.
• Lead the technical strategy and execution for the Gemini for Home conversational dialog stack across task-oriented and open-domain interactions.
• Optimize production conversational systems to deliver step-function improvements in end-to-end latency, reliability, execution safety, and real-world user…