- How do we develop code generation product(s) capable of solving many everyday developer tasks?
- What's the next big interface after autocomplete and chat for interacting with AI?
- How do we maintain reliability and scalability of our service across a wide range of IDEs, platforms, hardware, and programming languages?
- Ability to learn and become an expert quickly.
- A team player. Communicate well cross-functionally and does the most important thing for the company.
- A self-starter. Hunger to dream up, plan, design, build, and iterate on products independently. Work without the guidance of a product manager or designer.
- Extensive experience with frontend technologies such as Typescript and React. Familiarity with NextJS and TailwindCSS is a plus.
- Fluency building scalable, high throughput backend systems, infra, and databases.
- Strong product instincts and ability to iterate on low to medium fidelity mockups with the team.
- Previous experience working with WebSockets, Figma, streaming systems, gRPC, Postgres, and Golang is a plus.
- Familiarity with AI-powered developer tools like Codeium, Copilot, ChatGPT, and others is a strong plus.
- Our best work is done in person. The team goes in 5 days a week into our office in downtown Mountain View, CA (within walking distance of the Caltrain station, accessible 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.
- 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.
- Instruction and edit fine-tuned models for Codeium Command.
- Model inference performance optimization using Nvidia CUTLASS, CUDA C++, and PTX assembly language.
- Remote parsing, embedding, and indexing of users' codebases.
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Full Stack Product Engineer - Mountain View, United States - Codeium
Description
We're looking for a full stack product engineer to join us on our mission to build AI superpowers for developers.
About Codeium
In just over a year, Codeium has risen to become a leader in the AI developer tools space, giving hundreds of thousands of users around the world code autocomplete, in-editor chat assistants, and search. Our IDE extensions span 70+ programming languages and 40+ editors. Our state-of-the-art proprietary language models and custom inference stack allow us to deliver the best experience possible to our users. We've achieved substantial revenue and enterprise traction as proof of the quality and usefulness of our tools.
We're a small but experienced team that ships relentlessly. We welcome feedback to improve both our product and ourselves. We work hard, and we operate with a high degree of trust, agency, and ownership.
Challenges
(There are no hard requirements, as long as you can demonstrate you'll be able to write a lot of good code.)
Some of the things that our engineers have worked on recently: