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Edison Scientific

AI platform for scientific R&D workflows

Member of Technical Staff - AI Full-Stack Engineer

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • Software engineering experience with exposure to both backend and frontend development.
  • Strong proficiency in at least one backend language, such as Python or Node.js; the interview process requires Python.
  • Experience designing and consuming APIs, including FastAPI and REST; GraphQL is a plus.
  • Familiarity with frontend frameworks such as React or Next.js and modern web development practices.
  • Working knowledge of relational or document databases such as PostgreSQL, MySQL, or MongoDB.
  • Experience with version control, CI/CD pipelines, and basic automated testing.
  • Curiosity, a growth mindset, and eagerness to learn in a fast-moving environment.

Responsibilities

  • Design, implement, and maintain backend services, APIs, and databases that power the scientific discovery platform.
  • Contribute to frontend features and workflows, partnering with design and frontend teammates to deliver cohesive user experiences.
  • Build and extend data pipelines that support AI agents and research workflows.
  • Implement monitoring, observability, and automated testing to ensure system reliability and uptime.
  • Troubleshoot issues across the stack and proactively improve system quality.
  • Collaborate with engineering, design, and research teams to ship new AI-driven features and services.
  • Grow as a software engineer within a highly collaborative team working at the frontier of AI for science.

Desired Qualifications

  • Experience with data-heavy systems, scientific tooling, or ML/AI-adjacent platforms.
  • Prior work in startups or small teams with end-to-end ownership.

About the Company

Edison Scientific

AI platform for scientific R&D workflows

Edison Scientific provides an AI-powered platform that unifies research tasks in one environment. It combines literature synthesis, data analysis, molecular design, and the creation of publication-ready figures and reports so researchers can move from hypothesis to validated results without switching between many tools. The platform uses natural language processing and machine learning to digest scientific literature and data, automate workflows, and run tasks in parallel to speed up discovery. Compared with competitors, Edison Scientific stands out by offering an integrated, end-to-end R&D workflow that links literature, data, and design in a single platform, reducing manual handoffs and enabling scalable research. The company’s goal is to streamline R&D processes, shorten the time to insight, and help organizations rapidly validate findings and publish their work.

Company size
51-200
Company stage
Seed
Total funding
$70M
Headquarters
San Francisco, CA
Founded
2025

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