Technical Program Manager, Multimodal Generation

Snapshot

Google DeepMind is embarking on an ambitious initiative to build advanced world models—massive generative models capable of simulating physical environments. This groundbreaking effort is a critical step towards more capable and general AI systems. As a Technical Program Manager on the Multimodal Generation team, you will be at the heart of this initiative, leading complex, cross-functional programs to build, scale, and integrate these next-generation generative AI models.

About us

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

The Role

As a Technical Program Manager for Multimodal Generation, you will lead and drive complex, often undefined, programs to develop and scale our world models. You will be responsible for translating high-level strategy into actionable program plans, managing the end-to-end execution of these plans, and ensuring alignment across a diverse set of stakeholders. This role requires a strong technical background in AI, excellent program management skills, and the ability to navigate the challenges of large-scale research and engineering efforts. You will work closely with research scientists, engineers, and other teams to solve problems around training massive models, curating vast datasets, and integrating with multimodal AI systems like Gemini. Your work will be instrumental in powering future advancements in visual reasoning, planning for embodied agents, and real-time interactive entertainment.

Key responsibilities

• Program Leadership & Strategy: Lead complex and ambiguous programs focused on multimodal development. Partner with research and engineering leads to translate strategic goals into well-defined program plans, roadmaps, and success metrics.
• Large-Scale Execution: Drive the end-to-end execution of large-scale initiatives, including massive training runs, data curation pipelines, and model evaluation processes.
• Cross-Functional Integration: Act as a key liaison between the Multimodal team and other critical Google DeepMind projects, including teams working on Gemini, Robotics, Veo, Astra and Genie. Ensure seamless integration and alignment.
• Risk & Dependency Management: Proactively identify, assess, and mitigate risks and dependencies associated with large-scale model training and novel research directions.
• Process Improvement & Scalability: Develop and implement efficient processes and systems to manage training at a massive scale. Identify opportunities for automation and tooling to improve research and engineering velocity.
• Stakeholder Management: Build strong relationships and provide clear, consistent communication to stakeholders across research, engineering, and leadership.
• Technical Due Diligence: Perform technical due diligence to understand engineering scope, define milestones, and anticipate resource needs for ambitious research projects.
• Team Support: Provide proactive support to the team, and act as a mentor and point of escalation. Support rapid team and project growth and build processes to handle increasing numbers of contributors and project sub areas.

About you

In order to set you up for success as a Technical Program Manager at Google DeepMind, we look for the following skills and experience:

• Bachelor's degree in a technical field (Computer Science, Engineering, or related), or equivalent practical experience. A technical background is essential for navigating the complexities of this role.
• 5+ years of experience as a Technical Program Manager, Project Manager, or in a similar role, with a proven ability to lead and deliver complex, large-scale technical programs.
• Strong understanding of Artificial Intelligence (AI) principles, particularly in areas related to generative models, video, or large-scale model training.
• Experience working in a fast-paced, ambiguous, and research-driven environment.
• Proven ability to manage complex projects with multiple stakeholders and dependencies, demonstrating resourcefulness and creativity in solving novel challenges.
• Excellent communication, interpersonal, and influencing skills. Able to distill complex technical ideas for broad audiences, including leadership.
• Demonstrated ability to improve processes, workflows, and governance models to enhance efficiency within developme