Technical Program Manager, FAIR (AI Research)

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  • Meta
  • New York, NY
  • Full-Time
  • 2 weeks ago
  • $199,000/year to $272,000/year
Published
May 5, 2026
Location
New York, NY
Job Type

Technical Program Manager, FAIR (AI Research): our view in 3 lines...

  • The Role: Lead technical programs that coordinate researchers, engineers, product, and infrastructure teams to deliver compute, data, and generative AI solutions for FAIR research.
  • The Person: Drive end-to-end program management for compute infrastructure, data management, and generative AI projects, align cross-functional teams, guide technical strategy, and ensure milestones, reliability, scalability, and data quality are met.
  • Requirements: Requires a B.S. in Computer Science or related field, 10+ years of relevant technical or program management experience, and experience managing programs in compute infrastructure, data engineering, machine learning, or generative AI.

Job Description

As a Technical Program Manager (TPM) at FAIR, you will lead complex, cross-functional programs that accelerate scientific discovery and innovation at Meta. You will partner closely with researchers, engineers, product managers, and infrastructure teams to deliver scalable solutions across different initiatives. Your work will enable cutting-edge research and the development of state-of-the-art AI products and features.

Responsibilities

  • Drive end-to-end program management for technical initiatives spanning compute infrastructure, data management, and generative AI projects. Ensure alignment and execution across research, engineering, product, infrastructure, and operations teams
  • Collaborate directly with researchers to understand evolving requirements, workflows, and challenges. Co-design solutions that enable advanced experiments, model development, and scientific breakthroughs
  • Guide technical strategy, system architecture, and process improvements for compute systems, data pipelines, and generative model productionization. Identify and mitigate risks, resolve blockers, and ensure program milestones are met
  • Develop and implement best practices for reliability, scalability, data quality, and privacy. Support both technical and operational needs to ensure solutions are effective and adaptable
  • Facilitate regular communication, documentation, and feedback loops with all stakeholders, including leadership and external partners. Provide clear updates and ensure transparency as program needs evolve
Minimum Qualifications

  • B.S. in Computer Science or a related technical discipline, or equivalent experience
  • 10+ years of software engineering, systems engineering, hardware engineering, or technical product/program management experience
  • Experience managing technical programs in compute infrastructure, data engineering, machine learning, or generative AI, ideally in a research or lab environment
  • Organizational, communication, and stakeholder management skills, with demonstrated experience building partnerships across technical and research teams
  • Experience to work cross-functionally in a fast-paced, ambiguous environment
Preferred Qualifications

  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  • Experience evaluating model performance online and offline
  • Technical background in compute systems, data engineering, machine learning, or related fields is preferred
  • Familiarity with human data, machine learning datasets, RL environments, and generative model development is a plus

$199,000/year to $272,000/year + bonus + equity + benefits

Key Skills
? Key Skills in dark blue have been inferred based on similar industry roles
Compute Infrastructure Systems Architecture Risk Management Model Evaluation Strategy Leadership Stakeholder Management Machine Learning Program Management Data Management

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