Founding AI Engineer

83 Sciences uses AI to mine discarded experimental data for scientific breakthroughs. They are hiring a founding AI engineer to design insight extraction models and build tools for scientists. The role involves building multimodal pipelines, AI agents, and predictive models for materials discovery.

• Ship enterprise-ready products across our platform: data capture, structured experimental records, querying, and analysis tools. Build our AI systems: multimodal pipelines (vision models for handwritten notebook pages and drawn structures, speech-to-text at the bench), agents that reason over a lab's full experimental history, and models that predict outcomes and propose optimized process conditions. Work directly with research partners; watch scientists use what you built, then improve it. Help shape model architecture, data pipelines, and technical direction as an early team member. Build the data engine that turns messy experimental data (synthesis notes, PXRD, characterization) into training-grade datasets.

• 1+ years of experience managing technical projects at startups and team members or big companies / research labs (e.g., FAIR Chemistry, Google DeepMind, Microsoft Research, OpenAI, Anthropic Lila Sciences, MIT/Stanford/Berkeley/CMU/UToronto AI-for-science groups, or similar). Deep in at least two of: geometric deep learning (E(3)/SE(3)-equivariant GNNs), generative models (diffusion, flow matching), ML interatomic potentials. A track record of shipping enterprise-ready products to real users, end to end, with FDE / customer facing technical experience a plus. Comfort across the stack: you can get a feature all the way out the door & bias toward speed and ownership in a small, fast-moving team.