Computational and Experimental Scientist

ABOUT THE ROLE This is a full-stack scientist role at an early-stage AI-driven protein and peptide design company, sitting directly on a lean core team of 5 to 7 and reporting to the CEO. You will own the entire design-make-test-model loop, from sequences out of the inference platform to kinetics data back in, closing that loop end-to-end rather than handing off between functions. WHAT YOU'LL DO - Improve and extend pocket-conditioned discrete diffusion models and companion folding models, including refinements, new attention heads, and hierarchical reasoning. - Operate the AI inference stack at scale and diagnose usage patterns across signups, churn, and customer segments. - Own fluid-handling robotics and plate automation (Hamilton, Tecan, Opentrons, or equivalent), writing and shipping reliable protocols. - Own BLI and SPR end-to-end: assay design, immobilization, regeneration, referencing, dilution series, kinetic fitting, QC, and failure-mode diagnosis. - Write protocols for cloud labs and manage internal screening instrumentation. - Work the full stack across receptor biology, structure, scoring, and platform output. - Take sequences from the platform, run kinetics, update models, and ship improved sequences. WHAT WE'RE LOOKING FOR - 2+ years building or operating discrete diffusion models, protein language models (such as ESM or ProtT5), or structure prediction systems in an active design-make-test cycle, not just academic fine-tuning. - Personally written and debugged liquid-handler protocols on robotic platforms and shipped them to production. - Personally fitted BLI or SPR kinetic curves end-to-end and diagnosed failure modes such as mass transport, tip avidity, nonspecific binding, aggregation, or hook effect. - Fluent with sequence design tools (such as RFdiffusion or BindCraft) as inputs and outputs, not as black boxes. - Able to explain why a predicted ddG failed on a sensor and trace the root cause. - Proficient in Python or equivalent scripting for automation and kinetic curve fitting. - Strong background in biology, biochemistry, or life sciences, with receptor biology and protein structure literacy. - Operator mentality: resourceful, action-oriented, and comfortable executing under pressure at an early-stage company. - Background in gene editing, gene therapy, or receptor trafficking is a plus. - Prior experience at biotech accelerators or as an operator at a biotech startup or exit is a plus. COMPENSATION AND BENEFITS Initial consulting engagement: $3,000 to $5,000 per month. Full-time conversion: base salary of $80,000 to $200,000 depending on profile, with meaningful equity and deal-contingent upside. No visa sponsorship is available. LOCATION Hybrid, with increased on-site presence expected once internal screening infrastructure is established (roughly 3 to 6 months out). Primary location is San Francisco, California, US.