About the Team

Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity.  

The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture.

About the Role

As a Data Privacy Engineer, you will develop the tools and methods to enable safe and privacy-preserving operations with sensitive datasets. You will work alongside a diverse team of engineers, developers, and security advisers to design, architect, and drive privacy improvements across OpenAI. We are a small company and intend to stay small; the decisions you make today will have significant impact on the organization today and into the future.

In this role, you will:

• Design and develop tools, frameworks, and infrastructure that achieve OpenAI’s data privacy objectives.
• Innovate to solve novel privacy problems.
• Collaborate on cutting-edge AI research, and use AI to reduce OpenAI’s privacy risk.

You’ll make an impact on OpenAI by:

• Innovating on data privacy techniques.
• Use threat models to document privacy risks and scope mitigations.
• Evaluate privacy-preserving and data anonymization techniques for effectiveness.
• Test and measure OpenAI’s datasets for privacy compliance.
• Mitigating privacy vulnerabilities across OpenAI’s datasets and models.
• Developing tools and infrastructure that enable researchers to maximally leverage training datasets in a safe and secure manner.
• Collaborating with the Security, IT, Legal, Research, and Engineering teams to drive technical and policy improvements across data access, management, and governance.

You might thrive in this role if you have:

• Proficiency with programming (e.g. Python, Golang, or similar).
• Exposure to data processing frameworks (e.g. Apache Spark).
• Experience with public cloud providers (e.g. Amazon AWS, Microsoft Azure).
• Experience with statistical privacy techniques and methods (e.g. differential privacy, k-anonymity, data masking, etc).
• Exposure to privacy and compliance regulations including the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA).
• Ability to empathize and collaborate with colleagues, independently manage and run projects, and prioritize efforts for risk reduction.