Full-Stack Software Engineer

About 83 Sciences

AI-native materials discovery powered by unpublished experimental data

Tech description:

Our platform, Dalton, turns messy, heterogeneous lab data into structured, queryable knowledge. The technical problems we're working on include:

Multimodal data capture: OCR pipelines that convert handwritten lab notebook pages into structured entries and speech-to-text tools

Scientific data analysis: automated PXRD/characterization analysis: phase prediction, peak identification, anomaly detection

Chemistry-specific ML: models tuned on a lab's full experimental history (including failed runs) to predict synthesizability and reaction outcomes and suggest optimal process conditions

You'll work across the full stack (data pipelines, ML, and product) with real lab data and direct feedback from working scientists.

Job description:

We use AI to mine discarded experimental data and drive scientific breakthroughs. Working alongside labs, the goal is to collect the world’s experimental data into one platform.

**About 83 Sciences**

83 Sciences (YC S26) is the intelligence engine powering the future of research and materials discovery. Most experimental data (failed runs, unpublished results, raw instrument output) never gets captured. We turn raw lab signals into novel discoveries: capturing and structuring experimental data, shortening research processes, and surfacing the insights that drive new materials.

**The role**

We're hiring a full-stack engineer to build our next-generation electronic lab notebook and research platform. You'll work directly with the founders to design and ship products from the ground up. This is a high-ownership product engineering role (distinct from our Founding AI Engineer role, which owns the ML stack).

**What you'll do**

* Build features across the entire stack: experiment planning, laboratory inventory management, and integrated data analysis with Jupyter notebooks
* Ship AI-powered workflows, like digitizing handwritten lab notebooks into structured experimental records
* Turn ambitious ideas into polished, reliable software. Then, watch scientists use what you built and improve it
* As the platform grows, tackle advanced capabilities: spectroscopy analysis, intelligent search, and chemistry-specific tools

**What we're looking for**

* 1+ years of professional experience shipping production web applications end to end
* Strong with React/Next.js, TypeScript, Python, PostgreSQL, and modern cloud infrastructure
* You enjoy building products from scratch, work independently, and bias toward speed and ownership in a small, fast-moving team

**Nice to have:** mobile development, AI-powered applications, scientific software, or developer tools experience.

**Logistics:** NYC in-person (remote negotiable for the right person). US work authorization required.

If you're excited about using AI to transform how science is done, we'd love to hear from you.

Skills:

Amazon Web Services (AWS), PostgreSQL, Python, React, TypeScript, Next.js