About the Team

OpenAI's Core Data Systems ensures OpenAI gets access to timely, reliable and high quality data in order to train the AI models that align with our mission, namely developing safe and universally beneficial AGI. The team provides the data infrastructure for the OpenAI research organization. Projects like ChatGPT, plugins, browsing, code interpreter, GPT-V and others are aligned with human intent gathered by data, both human and synthetic. The volume of data in order to train our models has grown exponentially as we develop AI systems that are aligned with human interests.

Our team designs, deploys and maintains the data infra necessary to train and process high quality data at scale from a variety of sources and is responsible for the ML data management, and tooling that are leveraged to improve overall AI models. We use data from AI trainers to power alignment with the instruction following models and to train AI to leverage web browsing when answering questions. We harness high quality data from synthetic and human experts across a variety of domains and leverage OpenAI ML models to supercharge the data collection and quality process.

About the Role

In this role, you will:

• Architect, build, and deploy the data infra and back-end systems and services that power our data generation and management platform. 
• Collaborate closely with product managers, researchers, and the rest of our engineering team to create new products around emerging research capabilities and unsolved customer needs
• Iterate rapidly to improve user and developer experience while advancing scalability, performance, observability, and security

You might thrive in this role if you:

• Have meaningful experience with building (and rebuilding) production systems to deliver new product capabilities and to handle increasing scale
• Care deeply about the end user experience and take pride in building products to solve customer needs
• Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed
• Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done
• Build tools to accelerate your own (and your teammates’) workflows, but only when off-the-shelf solutions won’t do
• Are interested in and thoughtful about the impacts of AI technology (see our Charter for examples of our goals) and care deeply about the impact of ML models on people's lives; how to maximize the benefits and mitigate the possible harms.