Artificial intelligence will be one of humanity’s most transformative inventions. At 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.
Work with research and engineering teams to optimize subagent initiatives spanning Supervised Fine-Tuning (SFT) distillation, Reinforcement Learning (RL), and dynamic harnesses into clear goals, milestones, and release plans.
Partner with modeling and evaluation teams to monitor evaluation leaderboards, tracking latency, token usage, parallelization speedups, and quality improvements.
Drive convergence between research training harnesses and production agent runtimes, managing cross-functional dependencies across data, evaluations, infrastructure, and compute resources.
Contribute to technical proposals by analyzing multi-agent trajectories, sync vs. async delegation patterns, and overall performance headroom.
Manage end-to-end project planning using effective workflows, and translate complex modeling progress into clear, decision-ready updates for leadership and cross-functional audiences.
Minimum qualifications
Bachelor's degree in a technical field or equivalent practical experience.
8 years of experience in program management.
Preferred qualifications
8 years of program management experience driving delivery with research scientists and software engineers on foundation models, agentic systems, or RL pipelines.
Knowledge of software and ML development lifecycles, compute capacity planning, and experience managing complex, cross-functional dependencies.
Strong stakeholder management skills, with the ability to navigate ambiguity, influence outcomes, and align cross-functional teams without relying on direct authority.
Analytical depth in evaluating agentic trajectories, diagnosing failure modes, and translating insights into concrete data, harness, or RL interventions.
Bachelor's degree in a technical field or equivalent practical experience.
8 years of experience in program management.
