Computational and Experimental Scientist

Job description

### About the Role Join a lean team at an early-stage AI and biotech company, owning computational and experimental work across protein design and an inference platform. You will connect sequence design, laboratory testing, and model improvement in an end-to-end design-make-test loop. ### What You'll Do - Improve and extend discrete diffusion and protein folding models, including model refinements, attention mechanisms, and hierarchical reasoning. - Operate and scale an inference platform, and analyze usage patterns such as signups, churn, and customer segments. - Develop, debug, and maintain production protocols for liquid-handling robots and plate automation. - Design and run BLI and SPR assays, including immobilization, regeneration, referencing, dilution series, kinetic fitting, and quality control. - Write precise protocols for external laboratory partners and manage screening instrumentation. - Connect receptor biology, protein structure, scoring, and model outputs to practical scientific workflows. - Use experimental kinetics data to update models and improve designed sequences. ### What We're Looking For - Typically 3 to 11 years of relevant experience, including experience in biotech or scientific software roles such as solutions engineering, customer success, or a hybrid operator position. - Hands-on experience building or operating protein design, discrete diffusion, protein language, or structure prediction systems within an experimental design-make-test cycle. - Practical experience with tools such as ESM, ProtT5, RFdiffusion, BindCraft, or equivalent approaches. - Direct experience writing and debugging production methods for Hamilton, Tecan, Opentrons, or equivalent liquid-handling systems. - Hands-on BLI or SPR kinetic curve fitting, assay design, and diagnosis of assay failure modes. - Ability to code robot methods and analyze kinetic data using Python or equivalent scripting tools. - Understanding of biology, biochemistry, receptor biology, protein structure, and scoring functions, with the ability to investigate when predictions do not match experimental results. - Experience completing a full loop from sequence design through synthesis or expression and kinetics measurement to model updates and iteration. - Comfort with scientific customer engagement, including personalized outbound communication and navigating buying processes across organizations of different sizes. ### Compensation & Benefits Consulting engagement: $3,000 to $5,000 per month. Full-time conversion base salary: $80,000 to $200,000 annually, depending on experience, with equity and deal-contingent upside. Visa sponsorship is not available. ### Location Hybrid in New York, United States, with increased on-site presence expected as internal screening operations are established.