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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.
Job Responsibility:
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
Requirements:
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
Nice to have:
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