ABOUT THE TEAM The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. We push the boundaries of data, scaling laws, optimization techniques, model architectures, model + search co-design and efficiency improvements to propel our science. The Search team sits within Foundations, building agentic search by co-designing model-system interfaces with the core search stack: serving, indexing, and retrieval. We research and develop large-scale systems that transform and index vast corpora, enabling models to most effectively find and reason over information. In close partnership with researchers, we bring modeling advances into production and improve how AI systems discover, retrieve, and use knowledge. ABOUT THE ROLE We’re looking for a Researcher to lead our safety and alignment research: building the systems that distinguish useful web content from spam, manipulation, and other adversarial or low-quality material. The challenge extends beyond evaluating individual pages. A page may appear credible in isolation, while its links, metadata, or relationships with other sites reveal coordinated manipulation. As AI makes convincing content easier to produce at scale, detection systems must adapt to increasingly sophisticated adversaries. You’ll define the technical approach, build classifiers and evaluations, and shape how integrity signals influence what Search indexes and retrieves. Working closely with Search and broader Safety and Integrity teams, you’ll use frontier models to advance detection methods and bring them into production. RESPONSIBILITIES - Define the technical direction for Safety + Integrity, identifying gaps and determining which problems and interventions to prioritize. - Develop AI and ML systems to detect spam, scams, phishing, malicious domains, prompt injections, and other adversarial or low-quality web content. - Discover useful signals across page content, links, domains, metadata, and relationships between websites, including patterns that reveal coordinated manipulation. - Build evaluations that measure detection quality and how integrity interventions affect the information Search surfaces. - Translate detection signals into indexing, ranking, and filtering decisions, improving what models can retrieve and rely on. - Serve as the technical owner for integrity within Search, partnering with researchers, engineers, and broader Safety and Integrity teams to build and deploy these systems. YOU MIGHT THRIVE IN THIS ROLE IF YOU HAVE - Deep experience in web spam, search quality, adversarial content detection, or related integrity problems at scale. - Strong applied ML and research skills, with experience developing classifiers, detection methods, and evaluations for real-world systems. - An understanding of how adversaries manipulate content and links, coordinate across sites, and adapt to detection systems. - A track record of independently defining ambiguous technical problems and driving solutions from experimentation through production. - Experience working across research, engineering, and integrity teams while remaining hands-on with technical work. - A first-principles approach to using frontier models and compute, and a strong interest in keeping detection systems effective as adversaries evolve. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.  We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. 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