Software Engineer

Tetsuwan Scientific•San Francisco, CA

2d•Onsite

About The Position

Few fields touch human life as directly as biology does. But the pace of biological research is limited by how slowly and inconsistently experiments can be run by hand. We're building the infrastructure to make experimentation faster, more reproducible, and available to any scientist with questions worth asking. For decades we've had incredible robotic tools capable of executing experiments without countless tiring hours of pipetting by hand and these instruments are more precise and accurate than manual methods. But the engineering and validation time required to automate them means they're rarely used outside of the most repetitive, high-throughput research tasks. Our team has built a user-friendly editor and compiler that ingests a scientist's protocol description, converts it into a structured high-level format, and then automatically compiles it into executable code for these robots. See a demo here: https://tinyurl.com/mrx63phb We're a small, quickly growing team based in San Francisco. Joining now means shaping the product, the team, and the company at a stage where your decisions matter.

Requirements

3+ years building software professionally.
Demonstrated experience taking fuzzy ambiguous problems and turning them into working shipped features independently.
Comfortable jumping between languages and parts of the stack.
Excited to pick up new languages like OCaml.
Strong opinions about code, held loosely.
Desire to leave the codebase better than found it while balancing engineering momentum.
Enjoy working in-person with a small team where the line between product and engineering is blurry.

Nice To Haves

Experience or interest in domain specific languages, language design, and projectional editors.
Background in the life sciences, lab automation, or software work in any domain where the user is an expert in something you're not.
Experience with OCaml, or with other ML-family languages (Haskell, F#, Rust's type system, etc.).
Experience with Next.js, Tailwind, FastAPI, NeonDB, & Zustand.
Experience or interest in compilers, interpreters, heuristic algorithms and optimizing systems, especially unconventional and domain specific tools.
Familiarity with LLM-in-the-loop systems: parsing, structured extraction, evals.
Startup or small-team experience, especially earlier stage.

Responsibilities

Grow into working across the full stack (compiler, backend services, protocol editor).
Tackle complex engineering challenges involving compiler design and physical lab hardware.
Turn freeform scientific protocols into reliable robot instructions.
Decide how to model complex problems, ship solutions, and observe real scientists using the product.
Contribute to shaping the product, team, and company.