Related skills
validation genai production systems ml engineering data provenance📋 Description
- Design and ship production systems around models with data provenance and reliability.
- Lead discovery and scoping from pre-sales to post-sales with measurable endpoints.
- Define launch criteria for regulated contexts, with validation and audit readiness.
- Build in sensitive scientific data environments with access controls.
- Run evaluation loops to measure model quality against benchmarks.
- Distill deployment learnings into reference architectures and templates.
🎯 Requirements
- 5+ years in software/ML engineering or customer deployments in biotech/pharma.
- PhD, MS, or equivalent life sciences experience encouraged.
- Owned GenAI deployments end-to-end from scoping to production.
- Delivers AI in trial design or regulatory contexts with validation.
- Clear communication across scientific, clinical, and technical teams.
- Systems thinking; turn failures and audits into repeatable playbooks.
🎁 Benefits
- Hybrid work model with 3 days in the Paris office per week.
- Relocation assistance.
- Travel up to 50% of time.
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