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Member of Technical Staff, Full-stack

Edison Scientific
San Francisco, CA Full Time
POSTED ON 6/21/2026
AVAILABLE BEFORE 7/19/2026
About

Edison Scientific builds and commercializes AI agents for science. Scientific discovery moves too slowly, and autonomous AI agents are how we intend to fix that. We're assembling a team of top researchers and engineers across AI and biology to build an AI scientist.

Role

As a MTS (Full-stack, Backend-Focused, Python) you’ll help build and support our core platform that automates scientific discovery. You’ll work across the stack designing and building backend services, APIs, and data pipelines, while also contributing to user-facing features that make those capabilities accessible and intuitive.

Our mission is to build an AI scientist, and you’ll help build the tools, interfaces, and data systems it relies on. While this role leans heavily toward backend engineering, you’ll regularly collaborate with frontend engineers, designers, and researchers to deliver end-to-end functionality.

At Edison Scientific, full-stack engineering isn’t about doing “a little bit of everything.” It’s about owning features from concept to production, understanding how systems fit together, and building reliable foundations that accelerate humanity’s ability to ask bigger questions- and find answers faster.

This role is on-site at our San Francisco office in the Dogpatch neighborhood. Our office is a converted warehouse with high ceilings, open space, and a team that genuinely believes in what they're building.

This position is part of the Platform team.

Responsibilities

  • Design, implement, and maintain backend services, APIs, and databases that power the scientific discovery platform.
  • Contribute to frontend features and workflows, partnering closely 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.

Qualifications

  • Typically, 4-8 years of software engineering experience, with exposure to both backend and frontend development.
  • Strong proficiency in at least one backend language (e.g., Python, Node.js), with an interest in deepening backend expertise. (our interview process requires Python)
  • Experience designing and consuming APIs (FastAPI, REST; GraphQL a plus).
  • Familiarity with frontend frameworks (e.g., React, Next.js, or similar) and modern web development practices.
  • Working knowledge of relational or document databases (PostgreSQL, MySQL, MongoDB, or similar).
  • Exposure to cloud infrastructure (AWS, GCP, or Azure) and containerized environments (Docker; Kubernetes a plus).
  • Experience with version control, CI/CD pipelines, and basic automated testing.
  • Strong curiosity, a growth mindset, and eagerness to learn in a fast-moving environment.

Bonus points for

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

Salary

$175,000- $240,000

  • Offers equity

Why join us?

  • Competitive salary and equity
  • Full healthcare coverage — we pay 100% of premiums for you and your dependents
  • Support for growing families, including a yearly new parent stipend and fertility coverage through Carrot
  • 401(k) company matching
  • $300 health and wellness benefit
  • Lunch is on us every day you're in the office, and dinner is on us when you're working late
  • Regular team offsites and company events
  • A fast-moving, mission-driven culture where smart people do their best work and actually enjoy doing it

Compensation Range: $175K - $240K

Salary : $175,000 - $240,000

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