OpenAI· Security· San Francisco
Research Engineer, Privacy
Comp$380K – $445K
Classified Tasks (19)
Automate 0%Augment 74%Human-Only 26%
Augment (14)
AI assists, human decides
Design and prototype privacy-preserving machine-learning algorithms (e.g., differential privacy, secure aggregation, federated learning) deployable at OpenAI scale
technical
Measure model robustness against privacy attacks such as membership inference, model inversion, and data memorization leaks
analytical
Strengthen model robustness against privacy attacks while balancing utility with provable guarantees
technical
Develop internal libraries that implement privacy-preserving techniques for engineering and research teams
technical
Build evaluation suites to assess privacy properties and trade-offs of models and systems
technical
Produce documentation that makes cutting-edge privacy techniques accessible to cross-functional teams
communication
Publish insights from investigations to inform model-training and product-safety decisions
communication
Build production services that integrate privacy engineering capabilities into OpenAI systems
technical
Develop novel privacy-preserving techniques and approaches for deployment
creative
Equip cross-functional engineering and research partners with tools and resources to ensure responsible data use
operational
Investigate the interaction between privacy and machine learning to identify vulnerabilities and mitigation strategies
analytical
Develop techniques to improve data anonymization for datasets and model outputs
technical
Prevent model inversion and membership inference attacks through technical mitigations
technical
Implement the latest research in privacy-enhancing technologies such as differential privacy, federated learning, and defenses against data memorization
technical
Human-Only (5)
Requires human judgment
Lead deep-dive investigations into privacy–performance trade-offs of large models
leadership
Define and codify privacy standards, threat models, and audit procedures guiding the entire ML lifecycle
leadership
Establish audit procedures covering dataset curation through post-deployment monitoring
operational
Collaborate across Security, Policy, Product, and Legal to translate regulatory requirements into technical safeguards and tooling
communication
Safeguard user data while ensuring the usability and efficiency of AI systems
operational
Job description
Research Engineer, Privacy | OpenAI Careers ## Research Engineer, Privacy Security - San Francisco Apply now(opens in a new window) **About the Team** The Privacy Engineering Team at OpenAI is committed to integrating privacy as a foundational element in OpenAI's mission of advancing Artificial General Intelligence (AGI). Our focus is on all OpenAI products and systems handling user data, striving to uphold the highest standards of data privacy and security. We build essential production services, develop novel privacy-preserving techniques, and equip cross-functional engineering and research partners with the necessary tools to ensure responsible data use. Our approach to prioritizing responsible data use is integral to OpenAI's mission of safely introducing AGI that offers widespread benefits. **About the Role** As a part of the Privacy Engineering Team, you will work on the frontlines of safeguarding user data while ensuring the usability and efficiency of our AI systems. You will help us understand and implement the latest research in privacy-enhancing technologies such as differential privacy, federated learning, and data memorization. Moreover, you will focus on investigating the interaction between privacy and machine learning, developing innovative techniques to improve data anonymization, and preventing model inversion and membership inference attacks. **This position is located in San Francisco. Relocation assistance is available.** **In this role, you will:** * Design and prototype privacy-preserving machine-learning algorithms (e.g., differential privacy, secure aggregation, federated learning) that can be deployed at OpenAI scale. * Measure and strengthen model robustness against privacy attacks such as membership inference, model inversion, and data memorization leaks—balancing utility with provable guarantees. * Develop internal libraries, evaluation suites, and documentation that make cutting-edge privacy techniques accessible to engineering and research teams. * Lead deep-dive investigations into the privacy–performance trade-offs of large models, publishing insights that inform model-training and product-safety decisions. * Define and codify privacy standards, threat models, and audit procedures that guide the entire ML lifecycle—from dataset curation to post-deployment monitoring. * Collaborate across Security, Policy, Product, and Legal to translate evolving regulatory requirements into practical technical safeguards and tooling. **You might thrive in this role if you:** * Have hands-on research or production experience with PETs. * Are fluent in modern deep-learning stacks (PyTorch/JAX) and comfortable turning cutting-edge papers into reliable, well-tested code. * Enjoy stress-testing models—probing them for private data leakage—and can explain complex attack vectors to non-experts with clarity. * Have a track record of publishing (or implementing) novel privacy or security work and relish bridging the gap between academia and real-world systems. * Thrive in fast-moving, cross-disciplinary environments where you alternate between open-ended research and shipping production features under tight deadlines. * Communicate crisply, document rigorously, and care deeply about building AI systems that respect user privacy while pushing the frontiers of capability. **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