Research Scientist / Research Engineer, Search - Knowledge Graphs
OpenAI
Summary
We're looking for a Researcher to work on semi-structured knowledge graphs within Search. You'll research and develop methods for mining structured information from heterogeneous, unstructured and semi-structured web content, making that information more accessible and useful to AI models.
Job description
About the Role
We're looking for a Researcher to work on semi-structured knowledge graphs within Search. You'll research and develop methods for mining structured information from heterogeneous, unstructured and semi-structured web content, making that information more accessible and useful to AI models.
The core questions are: What structure helps models find and use information? How can we extract it reliably at web scale? And how do we measure whether it improves the model's ability to reason and answer questions? How do we design the system to be optimizable end-to-end?
You'll work across research, data, and systems, exploring how advances in AI and compute can improve the way knowledge is extracted, organized, and retrieved. This work will support retrieval across OpenAI products and internal research efforts, with opportunities for scientific publication.
Responsibilities
- Develop methods to extract and connect structured information across diverse web sources, including entities, attributes, and relationships.
- Build scalable approaches for transforming noisy, inconsistent content into useful knowledge representations.
- Explore how models and compute can improve extraction quality and reduce the manual work involved in building knowledge systems.
- Design evaluations that measure both the quality of extracted knowledge and its usefulness for retrieval and model reasoning.
- Partner with researchers and engineers to integrate structured knowledge into Search and use model performance to guide improvements.
You Might Thrive in This Role If You Have
- Deep experience in knowledge extraction, knowledge graphs, entity resolution, or related work that derives structure from large, heterogeneous datasets.
- Strong machine learning and research skills, with experience developing and evaluating methods for real-world data.
- A track record of building or scaling data and ML systems, particularly for web-scale extraction, indexing, or retrieval.
- Experience independently driving open-ended technical problems from an initial idea through experimentation and implementation.
- A first-principles approach to using AI and compute, with a willingness to rethink established methods as model capabilities improve.
- A strong interest in how the representation of information shapes what models can find, understand, and use.
Requirements
- Deep experience in knowledge extraction, knowledge graphs, entity resolution, or related work that derives structure from large, heterogeneous datasets
- Strong machine learning and research skills, with experience developing and evaluating methods for real-world data
- A track record of building or scaling data and ML systems, particularly for web-scale extraction, indexing, or retrieval
- Experience independently driving open-ended technical problems from an initial idea through experimentation and implementation
- A first-principles approach to using AI and compute, with a willingness to rethink established methods as model capabilities improve
- A strong interest in how the representation of information shapes what models can find, understand, and use
Benefits
- Medical Insurance
- Dental Insurance
- Vision Insurance
- Health Savings Account Contributions
- Flexible Spending Accounts
- Dependent Care FSA
- Commuter Benefits
- 401(k) With Employer Match
- Paid Parental Leave
- Paid Medical Leave
- Paid Caregiver Leave
- Paid Time Off
- Paid Company Holidays
- Paid Sick Time
- Mental Health Support
- Life Insurance
- Disability Coverage
- Learning and Development Stipend
- Office Meals
- Meal Delivery Credits
- Relocation Support
- Equity
- Performance-Related Bonuses
- Charitable Donation Matching
- Wellness Stipends
Company overview
OpenAI is an artificial intelligence research laboratory and company based in San Francisco, California. Founded in 2015 by Elon Musk, Sam Altman, Greg Brockman, Ilya Sutskever, Wojciech Zaremba, and John Schulman, OpenAI initially operated as a non-profit research organization before transitioning to a capped-profit model. The company's mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. OpenAI has developed groundbreaking AI technologies including GPT (Generative Pre-trained Transformer) models, DALL-E for image generation, and Codex for programming assistance. Their most notable product, ChatGPT, has revolutionized human-AI interaction and brought large language models to mainstream audiences. OpenAI conducts cutting-edge research in machine learning, natural language processing, computer vision, and reinforcement learning, while also developing practical AI applications that are transforming industries worldwide.