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Open nowFirst seen 2 days ago

AI Research Scientist (Technical Leadership)

Meta1,072 open roles

Where
Bellevue, WA
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Your applicationOpen nowAI Research Scientist (Technical Leadership)Meta · Bellevue, WA

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The clock on this job

Early applications get read.

8.5% of postings close within 7 days. Measured by our own scanner across the market. Meta postings stay open a median of 35 days.

Share of postings closed within
  1. 1.8%1 day
  2. 4.0%3 days
  3. 8.5%7 days
  4. 15.4%14 days
  5. 34.1%30 days
This job: first seen 2 days ago

Meta median: 35 days open

The posting

Meta's Monetization RankingAI Research team advances state-of-the-art AI technologies to optimize retrieval, ranking, bidding, and whole page optimization for Meta ads—driving significant annual revenue across Facebook and Instagram. We are seeking a distinguished AI Research Scientist at the technical leadership level to lead foundational and applied research for Ads AI systems. In this role, you will define the long-term research vision for Ads Ranking models, spanning areas such as generative retrieval, generative ranking, LLM-RecSys, large-scale model architectures, and ML systems co-design. You will shape research programs that influence Meta's advertising ecosystem and the broader AI research community, translating breakthrough findings into scalable, real-world impact.

Responsibilities

  • Define and champion a multi-year research vision for Ads AI systems, identifying transformative opportunities in areas such as generative ranking, whole page optimization, large-scale model architectures, and LLM-based recommendation systems
  • Lead the design and execution of novel AI research programs in retrieval and ranking, advancing state-of-the-art techniques for personalized ads delivery at scale
  • Architect end-to-end AI systems and modeling frameworks for ads ranking that establish extensible technical foundations and standards adopted across multiple research and engineering organizations
  • Drive research on next-generation sequence learning, graph-aware LLMs, AutoML, reinforcement learning, and causal learning for ads optimization
  • Lead research on ML systems and hardware-software co-design, including quantization, compression, ML compilers, and resource-efficient AI for next-gen hardware (GPUs, MTIA)
  • Define new evaluation metrics and experimental methodologies for long-term, cross-team AI research initiatives, connecting them to revenue and engagement priorities
  • Influence technical strategy and roadmap across multiple AI research teams and cross-functional partners, acting as a primary point of expertise for leadership
  • Produce high-impact publications at premier AI venues (NeurIPS, ICML, ICLR, KDD, WWW, ACL) and contribute to Meta's research reputation
  • Mentor and coach engineers and researchers across the organization, providing customized guidance on research design, modeling approaches, and career development
  • Partner with product, engineering, and infrastructure teams to translate research advances into reliable AI systems deployed at Meta's ads scale

Minimum Qualifications

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 12+ years of experience in AI research, spanning both foundational research and applied machine learning in an industry, academic, or government research setting
  • Demonstrated track record of leading AI research programs of significant scope, including defining research agendas and delivering results that advance the field
  • Extensive publication and citation history in peer-reviewed AI venues such as NeurIPS, ICML, ICLR, CVPR, ACL, or equivalent
  • Experience developing and deploying large-scale AI or machine learning systems, including deep expertise in areas such as large language models, generative models, multimodal learning, or AI reasoning
  • Experience communicating complex AI research strategy and technical decisions to diverse audiences, including research peers, engineering leaders, and executive stakeholders

Preferred Qualifications

  • Experience building and mentoring high-performing research teams, including developing researchers into cross-functional technical leaders
  • Experience with ads ranking, recommendation systems, or large-scale retrieval systems
  • Experience with generative models, LLMs for recommendation, reinforcement learning, or causal inference in production settings
  • Track record of industry-recognized contributions that have measurably influenced the direction of the AI research community
  • PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related technical field

US: $271,000/year to $347,000/year + bonus + equity

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