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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.
Responsibilities
- 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.
Requirements
- 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.
Skills
- Protein design
- Peptide design
- Diffusion models
- Folding models
- Inference platform operation
- User behavior analysis
- Liquid-handling robot protocols
- Screening automation
- Instrumentation management
- BLI assays
- SPR assays
- Kinetic fitting
- Quality control
- Assay failure diagnosis
- Model failure diagnosis
- Mass transport
- Nonspecific binding
- Aggregation
- Avidity
- Data quality
- Sequence design
- Kinetic measurement
- Model updating
- Customer support
- Scientific outreach
- Sales processes
- Protein language models (ESM, ProtT5)
- Design tools (RFdiffusion, BindCraft)
- Experimental iteration
- Liquid-handler method development
- Kinetic curve fitting
- Kinetic curve quality checking
- Python scripting
- Automation
- Kinetic data analysis
- Protein structure knowledge
- Receptor biology knowledge
- Scoring function knowledge
- Scientific communication
- Outbound sales
Location
- New York, New York, United States
Work Type
- Hybrid
Experience Level
- 3-11 years relevant experience
- 3+ years in biotech or life sciences software GTM, solutions engineering, or customer success
- 2+ years building or operating biological models
Salary/Compensations
- $3,000 to $5,000 per month (consulting)
- $80,000 to $200,000 (full-time base)
Benefits
- Equity
- Potential deal-contingent upside
About the Company
- AI-driven protein design biotech startup