Technical Program Manager, Cross-Product Execution and Model Feedback Operations, DeepMind

Google•Mountain View, CA

9d•$192,000 - $278,000

About The Position

DeepMind is hiring a Technical Program Manager to build and scale the operating model connecting its research teams with Google’s major product divisions. The role focuses on strategic cross-product coordination rather than day-to-day launch execution, helping product teams adopt frontier models and shared AI capabilities while channeling real-world product insights and evaluation signals back into research. The position connects model advancements with long-term product roadmaps so DeepMind and its product partners maintain shared technical goals and alignment on major company priorities. It involves coordinating research and product teams, structuring cross-organizational AI initiatives, and addressing dependencies and constraints. DeepMind describes its work as advancing AI for public benefit and scientific discovery, with safety and ethics as priorities. The listed US compensation is $192,000–$278,000, plus a 20% bonus target, equity, and benefits. Individual pay depends on job-related skills, experience, and relevant education or training.

Requirements

Bachelor’s degree in a technical field, or equivalent practical experience.
8 years of experience in program management.
Experience in technical program management, cross-functional collaboration, and software development.
Experience working with artificial intelligence or machine learning technologies.

Nice To Haves

8 years of experience managing cross-functional or cross-team projects.
Experience with modern LLMs, multimodal models, and agentic systems.
Experience with model training, evaluation design, and inference economics, including latency, cost, and compute capacity.
Experience building scalable operating models and repeatable processes across organizational boundaries.
Experience with AI platforms, data acquisition, and Software Development Life Cycle (SDLC) management.

Responsibilities

Partner with executive leadership across DeepMind and Google product divisions to align frontier research roadmaps, product strategy, and shared multi-year goals.
Define rules of engagement and manage a prioritized portfolio of cross-product AI initiatives; lead executive review forums focused on strategic prioritization, resourcing trade-offs, and cross-organizational alignment.
Connect real-world product insights with core research by establishing scalable frameworks for outcome-based evaluations and structured product feedback that inform future model development.
Accelerate adoption of frontier models across Google products by driving structured model lifecycle planning and shared AI foundations across multiple surfaces.
Synthesize model performance, infrastructure constraints, and roadmap dependencies across research and product teams to resolve cross-cutting bottlenecks and frame trade-offs for executive leadership.