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Open nowFirst seen 3 hours ago

AI Research Scientist, Ads Ranking

Meta1,033 open roles

Where
Sunnyvale, CA; New York, NY
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Your applicationOpen nowAI Research Scientist, Ads RankingMeta · Sunnyvale, CA; New York, NY

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Meta's own form.

The reply lands in your private mailbox

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The clock on this job

Early applications get read.

8.0% 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. 1.6%1 day
  2. 3.6%3 days
  3. 8.0%7 days
  4. 15.0%14 days
  5. 34.2%30 days
This job: first seen 3 hours ago

Meta median: 35 days open

The posting

Meta is seeking a Research Scientist to join our Ads Ranking organization. Individuals in this role are expected to be recognized experts in areas such as artificial intelligence, machine learning, and computational statistics, particularly including areas such as: sequential decision making, graph learning, reinforcement learning, deep learning, data representation and theory, and optimization. The ideal candidate will have an interest in producing new science to understand intelligence and technology to make computers smarter, and an equal interest in taking new research findings in this area and implementing them towards product needs.

Responsibilities

  • Identify and lead research on the most challenging and high-impact open problems in core machine learning, including areas such as optimization, generalization, representation learning, and scalable training
  • Develop novel machine learning algorithms, architectures, and theoretical frameworks that advance the state of the art and address previously intractable problems
  • Translate fundamental research findings into production-grade systems that deliver measurable improvements to Meta's AI-powered products and infrastructure
  • Define and drive the long-term technical vision and research roadmap for a core ML domain, gaining alignment across multiple research and engineering organizations
  • Establish extensible technical foundations, modeling standards, and evaluation frameworks that promote consistency and quality across research teams and product areas
  • Identify systemic gaps in existing ML approaches and develop invariants, benchmarks, and methodologies that prevent entire classes of modeling failures
  • Collaborate with research engineers, product teams, and infrastructure organizations to ensure research advances are operationalized at scale with reliability and efficiency
  • Communicate complex research findings through publications, technical reports, and presentations that serve as long-term reference points for the broader ML community
  • Mentor other researchers and engineers across the organization, providing customized technical guidance and fostering rigorous and innovative research practices
  • Monitor developments in the academic and industry ML landscape to identify emerging techniques and assess their relevance and risk to Meta's research strategy

Minimum Qualifications

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 12+ years of experience in machine learning research, including developing and publishing novel approaches in areas such as optimization, deep learning, representation learning, or related core ML domains
  • Track record of identifying and solving foundational machine learning problems that have resulted in measurable impact on large-scale AI systems or products
  • Experience defining multi-year research strategies and influencing technical direction across multiple teams or organizations
  • Experience translating theoretical machine learning research into production systems, including designing experiments, defining evaluation metrics, and connecting research outcomes to organizational priorities
  • Experience communicating complex machine learning concepts and research findings to both technical and non-technical audiences through publications, design documents, or technical presentations

Preferred Qualifications

  • Demonstrated ability to develop new debugging, evaluation, or verification methodologies that generalize across model families and prevent systemic failure modes
  • Experience leading cross-organizational research programs in large-scale model training, efficient inference, or foundational model architectures
  • Experience collaborating with applied research and product engineering teams to bring core ML advances from research prototype to global-scale deployment
  • History of publishing influential research in top-tier machine learning venues such as NeurIPS, ICML, ICLR, or equivalent, with demonstrated impact on the broader research community

US: $219,000/year to $301,000/year + bonus + equity

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