We're looking for AI Product Engineers to join us on our mission to build AI superpowers for developers.
What you'll do
- Propose and build AI-powered experiences for millions of developers, including professional software engineers for Fortune 500.
- Interface with complex, AI-powered systems, such as context retrieval and code generation, with emphasis on delivering efficient, scalable code.
- Demonstrate initiative and the ability to start and make progress on projects independently.
- Swiftly design, track, and analyze new product experiment results. Document findings and synthesize data with a drive to consistently improve.
About You
- Strong software engineering skills. Code reviews are a regular culture of the company.
- A team player and self-starter. Hunger to dream up, plan, design, build, and iterate on products independently without the guidance of a product manager or designer.
- Deep curiosity about the latest AI research and applications . You’re passionate about how AI can change software development and are motivated to turn these into a reality.
- Familiarity with AI-powered developer tools like Codeium, Copilot, ChatGPT, and others is a strong plus.
What we believe
- Our best work is done in person. The team goes 5 days a week into our office in downtown Mountain View, CA (within walking distance of the Caltrain station, commuter benefits from San Francisco).
- Engineers own projects end to end. No one knows the product better than the creator and they should drive brainstorming, design, iteration, and user research. We rarely do "handoffs."
- Research is in service of a better product. While we read many papers, we won't have time to write them. The best AI researchers have excellent software engineering skills and know that infrastructure and evaluation work are critical.
Recent projects
Some of the things that our engineers have worked on recently:
Regularly deploying an autocomplete and chat product that scales to hundreds of thousands of daily active users across 40+ IDEs.
Codeium Live: Chat in your browser with popular repositories.
An internal Kubernetes-native data processing framework to handle petabytes of data across thousands of spot CPUs.
A code attribution service for customers who want to ensure any generated code is licensed properly.
Remote parsing, embedding, and indexing of users' codebases.