Senior Computational and Experimental Scientist

About the Role

Join a lean team at an early-stage AI-driven biotech company, working across computational protein design, experimental biology, and scientific software. You will help close the design-make-test-model loop, using experimental results to improve models and deliver more useful sequences.

What You'll Do

• Refine discrete diffusion, protein language, and structure prediction models, including model architectures and constrained redesign workflows.
• Operate and improve a scientific inference platform, and analyze user behavior, usage patterns, and churn.
• Write, debug, and deploy protocols for liquid-handling robots and manage screening instrumentation.
• Run BLI or SPR assays end-to-end, from assay design and sample preparation through kinetic fitting and quality control.
• Diagnose experimental and computational failure modes, including mass transport, nonspecific binding, aggregation, and poor referencing.
• Design sequences, synthesize or express them, measure kinetics, update models, and iterate on improved candidates.
• Support scientific users and customer adoption with accurate, personalized outreach and an understanding of biotech buying processes.

What We're Looking For

• At least 2 years building or operating protein design, protein language, or structure prediction systems in a design-make-test workflow.
• At least 3 years in biotech or life sciences software go-to-market, solutions engineering, or customer success, including converting free users to paid offerings.
• Hands-on experience writing production methods for Hamilton, Tecan, Opentrons, or equivalent liquid handlers.
• Hands-on experience designing BLI or SPR assays, fitting kinetic curves, and troubleshooting assay results.
• Practical experience with tools such as ESM, ProtT5, RFdiffusion, BindCraft, or equivalents, plus Python or similar scripting for automation and data analysis.
• Biology, biochemistry, or life sciences knowledge, including protein structure, receptor biology, and scoring functions.
• Experience with scientific software users, biotech sales cycles, peptide design, protein engineering, or drug discovery is valuable.