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About the Role
Lead end-to-end deployments of AI models within life sciences organizations and research institutions, working with customers to translate real-world data and constraints into production systems. Measure success through production adoption, workflow impact, and feedback loops that inform product roadmaps. Collaborate with cross-functional teams to deliver in regulated contexts.
Responsibilities
- Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness.
- Lead discovery and scoping from pre-sales through post-sales, translating ambiguous needs into problem framing, system requirements, and execution plans.
- Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, and outcome metrics.
- Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture and operating procedures.
- Run evaluation loops to measure model and system quality against scientific benchmarks and use results to drive product changes.
- Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses for regulated life sciences environments.
Requirements
- 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software.
- Owned customer GenAI deployments end-to-end from scoping through production adoption.
- Delivered AI systems in trial design, regulatory writing, or scientific operations where validation strategy, auditability, compliance constraints, and reviewer expectations shaped system design and rollout.
- Communicate clearly across scientific, clinical, model research, technical, and executive audiences.
- Apply systems thinking with high execution standards, turning failures and escalations into improved operating standards and repeatable deployment playbooks.
Skills
- AI systems
- GenAI deployments
- Evaluation design
- Error analysis
- Iterative evidence generation
- Validation strategy
- Auditability
- Compliance constraints
- Systems thinking
- Execution standards
Location
- San Francisco
Work Type
- Hybrid (3 days in office per week)
- Travel up to 50% required
Experience Level
- 5+ years
Education Level
- PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged
Benefits
- Relocation assistance
About the Company
- OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity.
- We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products.
- AI is an extremely powerful tool that must be created with safety and human needs at its core.
- We must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
- We believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared.
Equal Opportunity
- We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
- Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates.
- We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.