Edison Scientific, a spinout of FutureHouse, aims to build an AI Scientist by scaling research, productizing it, and applying it to critical challenges such as drug development. The company is pioneering a new category by bringing AI Scientists to an industry accustomed to buying drug assets, not artificial intelligence.
Requirements
- High proficiency in one or more backend languages (e.g., Python, Node.js, etc.)
- Strong experience designing and building APIs (REST, GraphQL)
- Proficiency in databases (PostgreSQL, MySQL, MongoDB, or similar), with an understanding of schema design and query optimization
- Hands-on experience with cloud infrastructure (AWS, GCP, or Azure) and containerization/orchestration tools (Docker, Kubernetes)
- Hands-on experience with CI/CD pipelines, automated testing, and monitoring/observability tools (e.g., Prometheus, Grafana, Datadog)
- Experience with scientific computing, large-scale data pipelines, or ML/AI infrastructure
Responsibilities
- Design, implement, and maintain APIs, services, and databases scientific discovery platform.
- Implement monitoring, observability, and automated testing to maintain reliability and uptime.
- Troubleshoot and squash bugs.
- Collaborate with front-end, design, and research teams to build new AI agents and services.
- Be a member of a professional software engineer team working at the frontier of AI for science.
Other
- 3+ years of experience in backend software engineering
- Based in the San Francisco Bay Area or willing to relocate.
- In-Person
