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

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.
• - 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.

Minimum qualifications:

Preferred qualifications:

Qualifications

• 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.