A leading AI research company is seeking a privacy engineer in San Francisco. You will protect user data while ensuring AI system efficiency, employing techniques like differential privacy and federated learning. Responsibilities include designing privacy-preserving algorithms, investigating privacy-performance trade-offs, and developing documentation. Ideal candidates have experience with privacy technologies and deep learning. OpenAI promotes a diverse environment and offers relocation assistance.
Qualifications
Experience with privacy-preserving machine-learning algorithms.
Strong communication skills to explain complex concepts to non-experts.
Ability to work in fast-moving, cross-disciplinary environments.
Responsibilities
Design and prototype privacy-preserving machine-learning algorithms.
Measure and strengthen models against privacy attacks.
Develop internal libraries and documentation for privacy techniques.
Lead investigations into privacy-performance trade-offs.
Define privacy standards and audit procedures.
Collaborate with various teams to comply with regulatory requirements.
Skills
Hands-on research or production experience with privacy-enhancing technologies (PETs)
Fluency in modern deep-learning stacks (PyTorch/JAX)
Ability to stress-test models for private data leakage
Track record of publishing or implementing novel privacy or security work
Effective communication and documentation skills
Job description
A leading AI research company is seeking a privacy engineer in San Francisco. You will protect user data while ensuring AI system efficiency, employing techniques like differential privacy and federated learning. Responsibilities include designing privacy-preserving algorithms, investigating privacy-performance trade-offs, and developing documentation. Ideal candidates have experience with privacy technologies and deep learning. OpenAI promotes a diverse environment and offers relocation assistance.