The Video ML Foundations team optimizes video ranking infrastructure to balance latency, cost, and freshness for an optimal user experience. We drive diverse initiatives, including co-designing ranking models and systems, accelerating model training, optimizing GPU inference, and building funnel infrastructure and elastic compute. We are looking for candidates with an infrastructure background eager to apply systems and optimization methodologies to ranking systems. Our core focus is advancing state-of-the-art AI, ML, and RecSys technologies—spanning ranking, retrieval, model architecture, and optimization—to achieve long-term product goals.
- Develop and implement large-scale model architectures, leveraging model scaling and optimization techniques
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Collaborate with cross-functional teams to design and optimize ML systems, leveraging expertise in hardware-software co-design, including quantization, kernels, and resource-efficient AI, to drive performance improvements and efficiency gains
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Develop and implement innovative solutions for data-related challenges, utilizing knowledge of supervised learning, generative techniques, sampling, reinforcement learning, content understanding, and large language models
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Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
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Research experience in machine learning, deep learning, natural language processing, and/or recommender systems
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Experience with developing machine learning models at scale from inception to business impact
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Programming experience in Python and hands-on experience with frameworks such as PyTorch
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Experience with architectural patterns of large-scale software applications
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First author publications at peer-reviewed AI conferences (e.g., NeurIPS, ICML, ICLR, ICCV, CVPR, ACL, EMNLP, RecSys, KDD, WSDM, TheWebConf, ICDM, AAAI)
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PhD in AI, Computer Science, Data Science, or related technical fields
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Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
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Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
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Direct experience in generative AI, LLMs, RecSys, ML research
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Master's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
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Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at
[email protected].
$183,997/year to $257,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
