Role Overview

The Foundations Research team at OpenAI is at the forefront of high-risk, high-reward AI innovation. We're seeking a technical research lead to spearhead our embeddings-focused retrieval initiatives. In this role, you'll manage a team of elite researchers and engineers developing foundational technologies that enable AI models to retrieve and condition on relevant information precisely when needed.

Your work will span designing novel embedding training objectives, building scalable vector store architectures, and pioneering dynamic indexing methods. This technology will power retrieval across OpenAI's product suite and internal research, with ample opportunities for high-impact publications and deep technical contributions to frontier models.

Based in San Francisco with a hybrid model (3 days/week in office), this position offers relocation assistance and positions you at the cutting edge of AI foundations research.

Key Responsibilities

As Foundations Retrieval Lead, you'll:

• Lead cutting-edge research on embedding models and retrieval systems optimized for grounding, relevance, and adaptive reasoning in large language models
• Build and manage a high-performance team developing end-to-end infrastructure for embedding training, evaluation, and integration into frontier models
• Innovate across dense, sparse, and hybrid representation techniques, advancing metric learning and learning-to-retrieve paradigms
• Collaborate with Pretraining, Inference, and Applied teams to embed retrieval capabilities throughout the AI model lifecycle
• Shape OpenAI's vision for memory-augmented AI systems leveraging learned representations
• Design scalable architectures handling petabyte-scale vector stores for production deployment
• Mentor researchers through the publication process at top AI conferences
• Drive efficiency improvements enabling real-time retrieval at unprecedented scales
• Challenge conventional wisdom on retrieval-memory interactions in transformer architectures
• Bridge theoretical research with practical engineering for immediate product impact
• Identify and pursue moonshot research directions in AI foundations
• Represent OpenAI at industry events and academic collaborations
• Scale embedding pipelines from research prototypes to production systems serving millions

Qualifications

Successful candidates will demonstrate:

• Proven leadership of ML research or infrastructure teams delivering production impact
• Deep expertise in representation learning, embedding models, or vector retrieval systems
• Strong understanding of transformer LLMs and embedding-language model interactions
• Research track record in contrastive learning, metric learning, or embedding objectives
• Experience scaling large ML systems, particularly embedding pipelines
• First-principles approach to AI system design and evaluation
• PhD in CS/ML or equivalent research experience preferred
• 5+ years in AI research leadership roles
• Top-tier conference publications in relevant areas
• Cross-functional collaboration experience with model training teams

Salary & Benefits

Salary Range: $450,000 - $750,000 USD annually (depending on experience and qualifications), plus significant equity.

Comprehensive Benefits Package:

• Industry-leading medical, dental, vision coverage
• 401(k) with generous company match
• Unlimited PTO policy
• Hybrid SF work model with relocation support
• Parental leave and family benefits
• Professional growth stipend
• Onsite meals, gym reimbursement, commuter benefits
• Equity package with potential for substantial growth

This compensation positions OpenAI among the most competitive in AI research.

Why Join OpenAI?

OpenAI isn't just building AI—we're defining its future. As Foundations Retrieval Lead, you'll:

• Work on high-stakes research shaping the next decade of AI capabilities
• Lead a team tackling problems at the frontier of human knowledge
• Publish breakthrough research advancing global AI understanding
• Impact billions through products powered by your retrieval innovations
• Join a mission-driven culture prioritizing safety and human benefit
• Collaborate with the world's top AI talent daily

OpenAI's commitment to equal opportunity ensures diverse perspectives drive our mission success.

How to Apply

Ready to lead the future of AI retrieval? Submit your application including:

• Resume/CV highlighting leadership and technical achievements
• Research portfolio or key publications
• Statement of research interests in embeddings/retrieval
• References from ML research collaborators

OpenAI's hiring process includes technical interviews, research discussions, and leadership assessment. We prioritize mission alignment and technical excellence.

OpenAI is an equal opportunity employer committed to diversity.