About Us
We're building a cutting-edge AI research suite that accelerates science in medicine, AI, climate, and more.
Our system streamlines every stage of academic discovery by connecting papers, ranking relevance, summarizing insights, and mapping citations.
This is a hands-on role with real ownership. You will move fast, experiment, and ship production systems that impact thousands of researchers worldwide.
Key Responsibilities:
* Design and deploy scalable APIs and services capable of serving hundreds of concurrent requests.
* Architect, implement, and productionize vector databases and embedding-based retrieval systems.
* Work on GenAI integrations including react agents, graph agents, prompt engineering, and LLM orchestration.
* Set up full-stack search engines from scratch that can handle real-world academic workloads.
Requirements:
* Strong background in semantic search, vector databases, LLM frameworks, agent-based systems, and document retrieval.
* Skilled in Python for backend development with the ability to build scalable APIs and services.
* Past experience deploying systems at scale, including search engines, retrieval pipelines, or embedding models.
* Ability to design infrastructure that serves hundreds of concurrent requests.
* A research-driven and pragmatic mindset with a focus on measurable outcomes.