Forward Deployed Engineer (FDE), Life Sciences – SF
Location
San Francisco
Employment Type
Full time
Location Type
Hybrid
Department
Model Deployment for Business
Compensation
- $198K – $335K • Offers Equity
The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.
Benefits
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Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
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Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
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401(k) retirement plan with employer match
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Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
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Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
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13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
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Mental health and wellness support
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Employer-paid basic life and disability coverage
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Annual learning and development stipend to fuel your professional growth
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Daily meals in our offices, and meal delivery credits as eligible
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Relocation support for eligible employees
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Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.
About the team
OpenAI’s Forward Deployed Engineering team partners with global pharma and biotech, CROs, and research institutions to deploy existing expertise across the R&D value chain to help customers design and ship production-grade AI systems. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments.
About the role
We are hiring a Forward Deployed Engineer (FDE) to push the frontier on what is possible today across drug discovery (e.g., target identification, molecular design, pre-clinical) and development (e.g., trial design, trial ops, biostats) by leading end-to-end deployments of our models inside life sciences organizations and research institutions. You will work with customers who are deep experts in their scientific or operational domains, translating real-world data, infrastructure, and constraints into production systems.
Responsibilities
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Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows.
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Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and an execution plan with measurable endpoints.
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Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until we demonstrate sustained production impact.
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Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling.
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Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use results to drive model and product changes.
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Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments.
Requirements
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Bring 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software; PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged.
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Have owned customer GenAI deployments end-to-end from scoping through production adoption, and improved them through evaluation design, error analysis, and iterative evidence generation that tightens acceptance criteria over time.
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Have 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.
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Communicate clearly across scientific, clinical, model research, technical, and executive audiences, translating technical tradeoffs into decision quality, risk posture, and measurable outcomes with credibility.
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Apply systems thinking with high execution standards, consistently turning failures, escalations, and audit findings into improved operating standards, validat
