Senior Computational and Experimental Scientist

About the Role

Join a lean team at an AI-driven protein design biotech startup and own the computational and experimental workflows behind its protein and peptide design platform. You will connect model development, customer use, laboratory testing, and kinetic data to improve designs and support platform growth.

What You'll Do

• Improve protein and peptide design, diffusion, and folding models through architectural refinements, hierarchical reasoning, and active learning.
• Operate and refine an inference platform at scale, investigate user behavior and churn, and help convert free-tier users into paying customers.
• Write, debug, and deploy production protocols for liquid-handling robots and manage screening automation and instrumentation.
• Design and run BLI and SPR assays end to end, including immobilization, regeneration, referencing, dilution series, kinetic fitting, and quality control.
• Diagnose assay and model failures, including mass transport, nonspecific binding, aggregation, avidity, and data quality issues.
• Close the design-make-test-model loop by designing sequences, measuring kinetics, updating models, and iterating on improved candidates.
• Support scientific customers through personalized outreach and sales processes ranging from small biotech teams to large pharmaceutical organizations.

What We're Looking For

• Three to eleven years of relevant experience, including at least three years in biotech or life sciences software GTM, solutions engineering, or customer success, with experience converting free users to paid plans.
• Hands-on wet-lab experience and at least two years building or operating biological models in a practical design-make-test workflow.
• Experience with protein language models such as ESM or ProtT5, and design tools such as RFdiffusion or BindCraft, as part of real experimental iteration.
• Personally developed and deployed liquid-handler methods, and independently fitted and quality-checked BLI or SPR kinetic curves.
• Python or equivalent scripting skills for automation and kinetic data analysis, with knowledge of protein structure, receptor biology, and scoring functions.
• Strong scientific communication skills and the ability to conduct 30 to 50 personalized, scientifically accurate outbound touches per day.