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Urgent! Technical Program Manager, RL Infrastructure & Reliability Job Opening In Mountain View – Now Hiring Google
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
Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf.
For more information on how we handle your data, please see our Applicant and Candidate Privacy Policy (https://careers.google.com/privacy-policy/) .
At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact.
We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law.
If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.
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Unlock Your Technical Program Potential: Insight & Career Growth Guide
Real-time Technical Program Jobs Trends in Mountain View, United States (Graphical Representation)
Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph below. This graph displays the job market trends for Technical Program in Mountain View, United States using a bar chart to represent the number of jobs available and a trend line to illustrate the trend over time. Specifically, the graph shows 51677 jobs in United States and 283 jobs in Mountain View. This comprehensive analysis highlights market share and opportunities for professionals in Technical Program roles. These dynamic trends provide a better understanding of the job market landscape in these regions.
Great news! Google is currently hiring and seeking a Technical Program Manager, RL Infrastructure & Reliability to join their team. Feel free to download the job details.
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An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Google adheres to the cultural norms as outlined by Expertini.
The fundamental ethical values are:The average salary range for a Technical Program Manager, RL Infrastructure & Reliability Jobs United States varies, but the pay scale is rated "Standard" in Mountain View. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.
Key qualifications for Technical Program Manager, RL Infrastructure & Reliability typically include Other General and a list of qualifications and expertise as mentioned in the job specification. Be sure to check the specific job listing for detailed requirements and qualifications.
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