Technical Program Manager, Physical AI and Creative Technologies, DeepMind

As a TPM in Frontier Research, you will help scale two high-priority research areas. Within the Physical AI space, you will work alongside research leadership, sharpening strategy, building scalable roadmaps, and driving execution as the portfolio grows. Within Creative Technologies, you will help turn bold, frontier research ideas into proven breakthroughs and build the bridges that bring them into our mainline models. Across both, you will navigate immense technical complexity, manage critical cross-functional dependencies, perform engineering due diligence, and accelerate the path from research idea to model impact. This role demands an exceptional ability to provide clarity within ambiguous environments and implement creative solutions in a fast-paced, competitive scientific landscape.

You will partner with Research Leads to bring structure, strategy, and momentum to a growing body of research on AI that perceives, understands, and interacts with the physical world. You will own program planning, cross-team alignment, and execution across a different and fast-moving portfolio.

You will help drive blue-sky, frontier research in media generation and agents for media creation, pushing the state of the art in how models generate and refine images, video, and audio. You will help take ambitious ideas from early exploration to proven results, land them, and push them into our mainline models, partnering closely with core modeling teams on priorities and landing timelines.

Technical knowledge in robotics, world models, media generation, AI agents, or multimodal model development is beneficial but not required; curiosity and the ability to ramp quickly on deep technical topics are essential.

Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $192000 - $278000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google . Responsibilities

• Translate complex research and engineering efforts into execution plans and measurable goals to actively drive delivery. Build and optimize scalable operational frameworks to monitor program performance and anticipate technical risks.

• Engage deeply with model architectures, training, and data to establish roadmaps and influence technical direction.

• Build and guide effective cross functional partnerships across different disciplines (research, modeling, data, infrastructure, evaluation, responsibility, safety) and partner teams across Google, to ensure alignment on shared objectives.

• Identify and implement opportunities to enhance research velocity and engineering excellence through optimized tools and methodologies.

• Drive strategic planning for mission-critical resources (compute and data management, allocation) to respond to a rapidly changing competitive landscape.

Minimum qualifications:

• Bachelor’s degree in Computer Science, Engineering, a related technical field.

• 8 years of experience in technical program management in a technical or research environment.

• Experience in machine learning and working with researchers and engineers on model design, training, data, and evaluation.

Preferred qualifications:

• Experience driving generative model research from early exploration through to measurable results.

• Experience landing research into production models or products, working across research and core modeling teams on data, evaluations, integration.

• Experience with AI agents or agentic systems, or with physical AI areas (i.e. robotics, embodied AI, world models, simulation).

• Track record of building programs from 0-1 in ambiguous, rapidly evolving technical spaces.

• Strong problem-solving skills, and ability to understand technical systems and identify opportunities for optimization.

• Passion for the future of AI and the ability to grow in a dynamic, fast-paced environment where technology meets real-world impact.