Technical Program Manager, RL Infrastructure & Reliability

The Role
As a Technical Program Manager for Reinforcement Learning (RL) Infrastructure & Reliability, you will focus on a critical, rapidly evolving area: the post-training stack that refines and improves Gemini models. You will be a hands-on driver of technical programs, embedding with engineering teams to enhance the reliability, performance, and scalability of the infrastructure that powers our most advanced RL workloads.

This role is for a TPM who thrives on ambiguity and technical depth. You will lead concrete engineering initiatives, from driving performance optimization programs to owning the execution of reliability roadmaps. Your work will have a direct and measurable impact on the quality of our models and the velocity of our research.

Responsibilities

• Performance & Efficiency Optimization: Drive technical programs focused on optimizing the performance and efficiency of post-training and RL workloads. This includes quantitative analysis, developing shared dashboards, and guiding engineering execution on improvements.
• Reliability Roadmap Execution: Execute key projects from the post-training reliability roadmap, such as improving monitoring tools and centralizing core services, to enhance the stability of the entire stack.
• Code Health Initiatives: Own the technical project management for initiatives aimed at improving the long-term health, testability, and maintainability of the RL infrastructure codebases.
• Roadmap & Backlog Management: Manage the engineering backlog and tactical execution for core RL framework development, ensuring progress is tracked and aligned with the team's strategic roadmap.
• Cross-Functional Coordination: Build effective working relationships with engineering teams, guiding alignment on project goals, managing interdependencies, and ensuring clear communication and risk management.
• Program Governance: Contribute to the broader program management of the Frameworks and Infrastructure team, providing clear stakeholder updates and supporting team-wide events.

Minimum Qualifications

• Bachelor's degree in a technical field or equivalent practical experience.
• 5 years of experience in program or project management in a technical software environment.
• Experience working directly with engineering teams on the software development lifecycle.

Preferred Qualifications

• 5+ years of relevant work experience.
• Experience with machine learning workflows, particularly in training, post-training, or MLOps. Direct experience with Reinforcement Learning (RL) is a strong plus.
• Strong analytical skills, with experience in performance analysis, reliability engineering (SRE), or technical efficiency projects.
• Proficiency with project management and development tools (e.g., Jira, Gantt charts) for managing technical backlogs.
• Excellent interpersonal and communication skills, with a demonstrated ability to work effectively in ambiguous, fast-paced R&D environments.

The US base salary range for this full-time position is between $156,000 - $229,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

Application deadline: 12pm PST Friday 14th Nov 2025

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