Founding AI/ML Engineer - Build Lab Discovery Tools

83 Sciences; New York (NY); On-site; USD 130,000 - 180,000; Full time

Job summary

83 Sciences in New York City is seeking a founding AI engineer to design insight and discovery extraction models and ship tools for scientists. You’ll own the architecture and build the ML stack alongside our Chief Science Officer and work directly with the founders.

You will ship enterprise-ready products across our platform, develop multimodal AI systems, and shape data pipelines and technical direction as an early team member. NYC in-person collaboration expected.

Qualifications

• 1+ years of experience managing technical projects at startups or large research labs.
• Deep in at least two: geometric deep learning, generative models, or ML interatomic potentials.
• Track record shipping enterprise-ready products to real users, end-to-end.
• Comfort across the stack with ownership in a small, fast-moving team.

Responsibilities

• Ship enterprise-ready products across our platform: data capture, structured experimental records, querying, and analysis tools.
• Build our AI systems: multimodal pipelines, agents that reason over a lab's full history, and predictive models.
• Work directly with research partners and scientists to iterate based on real usage.
• Help shape model architecture, data pipelines, and technical direction as an early team member.
• Build the data engine that turns messy experimental data into training-grade datasets.

Skills

Project management

End-to-end product shipping

Ownership mindset

Geometric deep learning

Generative models

ML interatomic potentials

Job description

83 Sciences in New York City is seeking a founding AI engineer to design insight and discovery extraction models and ship tools for scientists. You’ll own the architecture and build the ML stack alongside our Chief Science Officer and work directly with the founders.

You will ship enterprise-ready products across our platform, develop multimodal AI systems, and shape data pipelines and technical direction as an early team member. NYC in-person collaboration expected.