Full Stack Engineer

About Comet

Comet is building the development platform for teams who want to ship robust, reliable, and responsible AI applications. Opik, our open source LLM evaluation framework, has quickly become one of the most popular tools in the space. Our experiment management platform is used by data scientists at companies like Uber, Netflix, and Etsy. Tens of thousands of researchers, engineers, academics, and hobbyists use Comet every day to build the future of AI. 

Working at Comet will give you access to the most exciting work being done in all areas of machine learning. Some of the top researchers and companies working on self-driving cars, drug discovery, particle research, diffusion models, and LLMs use Comet every day. Your work has the potential to accelerate the development of some of the most impactful technology in the world, and you will be doing it alongside a team of passionate, caring individuals. If that sounds exciting, Comet is the right place for you.

Comet is backed by more than $63 million in venture capital funding and powers some of the best machine-learning teams in the world, including Netflix, Uber, Etsy, and Mobileye. We are a remote-first company with offices in New York City (USA) and Tel Aviv (Israel).

You are:

We are seeking a talented Full Stack Engineer to join our team and help build the Opik product! Opik is an open-source platform designed to streamline the entire lifecycle of LLM applications, helping developers evaluate, test, monitor, and optimize their models and agentic systems.

Ready to shape the future of LLM development? Join us in building the next generation of AI observability tools!

Responsibilities:

• Build & ship features at high pace in a fast-moving AI development environment
• Develop and maintain comprehensive observability tools for LLM applications and RAG systems
• Create intuitive user interfaces for LLM tracing, evaluation dashboards, and production monitoring
• Build robust APIs and backend services to support real-time LLM application monitoring
• Collaborate with AI researchers and ML engineers to implement cutting-edge evaluation methodologies
• Contribute to both frontend (React/TypeScript) and backend (Java) components
• Design and implement automated evaluation systems and "LLM as a Judge" capabilities
• Work on integrations with popular LLM frameworks and libraries
• Participate in open-source community engagement and technical documentation

Requirements: