Member of Technical Staff - Forward Deployed Scientist
$170,000–$275,000 year
On-siteSouth San Francisco, California, United States
Job Summary
Construct bio environments for AI agents by building and curating biomedical skills, tools, databases, and data integrations. Design evaluation pipelines and benchmarks to validate scientific accuracy, then deliver solutions directly to enterprise customers in biotech and pharma. Run training sessions, scope high-stakes projects, and own delivery from hypothesis to production while serving as the scientific voice in feedback loops. This role requires a PhD in a relevant field with deep expertise in discovery, IND-enabling, or clinical translational areas, plus strong engineering skills for working with biological data at scale. Based in South San Francisco with some customer travel, the position offers competitive equity and full medical benefits.
Required Qualifications
- PhD training in a relevant field (or MD/PhD or equivalent), with strong command of common biomedical tools, databases, and analytical workflows
- Industry experience in biotech or pharma (computational biology, bioinformatics, or a closely related function)
- Solid engineering skills: writing code, building pipelines, and working with biological data at scale
- Comfort working directly with enterprise customers and translating their scientific needs into technical requirements, including running training sessions
- A strong communicator who can explain complex ideas clearly to both scientists and executives
- Ability to move quickly in a fast-paced research and product environment
- Deep expertise in at least one of the following areas (and comfort collaborating across the others): Discovery, IND-Enabling (preclinical), Clinical & Translational
Desired Qualifications
- AI-native working style; fluent with modern AI coding tools and agent-based workflows
- Experience with LLMs, agents, or AI/ML systems applied to biomedical problems
- Familiarity with foundation models: genomic foundation models, protein language models, or vision models for pathology/imaging
- Depth in more than one of the three areas above, or breadth across multiple biomedical domains (genomics, proteomics, drug discovery, clinical data)
- Area-specific strengths, such as: structure-based and generative design of small molecules or proteins, e.g. docking, RFdiffusion, ProteinMPNN, ESM (Discovery); PBPK or QSP modeling, e.g. Simcyp, GastroPlus, NONMEM (IND-Enabling); epidemiology / biostatistics, CDISC data standards, digital biomarkers (Clinical & Translational)
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