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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and deploying AI systems within regulated environments, ensuring compliance and validation while effectively communicating across diverse audiences. Proven ability to lead customer-facing projects from scoping to production adoption in biotech and clinical research.
Highest-signal resume keywords
Software EngineeringMachine Learning EngineeringCustomer GenAI DeploymentsValidation StrategyRegulatory Compliance
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Evaluation DesignError AnalysisIterative Evidence GenerationTrial DesignScientific OperationsData ProvenanceSystem RequirementsExecution PlansAudit ReadinessOutcome Metrics
Soft Skills
Communication Across AudiencesSystems ThinkingHigh Execution Standards
Certifications & Qualifications
PhDMS
Industry Keywords
BiotechPharmaClinical ResearchScientific SoftwareRegulated Contexts
About the role
Key responsibilities & impact- Design and ship production systems around models
- Own integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows
- Lead discovery and scoping from pre-sales through post-sales
- Translate ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and execution plans with measurable endpoints
- Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, and outcome metrics
- Drive delivery until sustained production impact is demonstrated
- Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling
- Run evaluation loops against workflow-specific scientific benchmarks
- Use evaluation results to drive model and product changes
- Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses
Requirements
What you’ll need- 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software
- Experience owning customer GenAI deployments end-to-end from scoping through production adoption
- Experience with evaluation design, error analysis, and iterative evidence generation
- Experience delivering AI systems in trial design, regulatory writing, or scientific operations
- Experience with validation strategy, auditability, compliance constraints, and reviewer expectations
- Ability to communicate across scientific, clinical, model research, technical, and executive audiences
- Systems thinking and high execution standards
- PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged
Benefits
Comp & perks- Equity
- Performance-related bonus(es) for eligible employees
- Medical, dental, and vision insurance for you and your family
- Employer contributions to Health Savings Accounts
- Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
- 401(k) retirement plan with employer match
- Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents)
- Paid medical and caregiver leave (up to 8 weeks)
- Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
- 13+ paid company holidays
- Multiple paid coordinated company office closures throughout the year
- Paid sick or safe time
- Mental health and wellness support
- Employer-paid basic life and disability coverage
- Annual learning and development stipend
- Daily meals in offices
- Meal delivery credits as eligible
- Relocation support for eligible employees
- Charitable donation matching
- Wellness stipends may also be provided