Director of AI Engineering – Vaccine R&d Operations Enablement

Pfizer Pfizer · Pharma · New York, NY

Director of AI Engineering role focused on applying AI automation and advanced analytics in regulated healthcare R&D operations. The role involves leading the definition and delivery of AI solutions for lab and office workflows, strengthening operational decision-making through predictive models, enabling regulated AI systems with governance, optimizing development planning, and engineering/scaling production-grade ML platforms. Requires expertise in predictive modeling, optimization, automation, generative AI, and ML system design, with strong programming skills in Python and ML frameworks, and experience scaling models in cloud/HPC environments. Collaboration across scientific, operational, quality, and business teams is critical.

What you'd actually do

  1. Define and deliver AI solutions that support process-heavy lab and office workflows, including experiment tracking, documentation, handoffs, and operational reporting.
  2. Develop predictive, optimization, and scenario-based models to support resource planning, capacity management, timeline forecasting, and risk trade-offs.
  3. Design AI solutions aligned with GxP expectations, data integrity standards, and inspection readiness, supporting deviation monitoring, CAPA trending, documentation completeness, data genealogy, and audit preparedness.
  4. Architect and deploy robust, production-ready ML and analytics pipelines with appropriate governance, reproducibility, and monitoring.
  5. Act as a strategic bridge between technical teams and scientific, operational, quality, and business stakeholders to ensure adoption and measurable value.

Skills

Required

  • PhD or Master's degree in a relevant field
  • 5-7 years of applied analytical experience
  • 2 years of AI/ML experience in a relevant domain
  • Strong understanding of process-heavy environments
  • Expertise in predictive modeling
  • Expertise in optimization
  • Expertise in automation
  • Expertise in generative AI
  • Expertise in ML system design
  • Strong programming skills in Python
  • Experience with modern ML frameworks (PyTorch, TensorFlow)
  • Experience scaling models in cloud and/or HPC environments
  • Experience collaborating across scientific, operational, quality, and business teams
  • Clear communication skills

Nice to have

  • Experience in life sciences, pharma, R&D, clinical operations, or other regulated industries
  • Financial and business experience supporting budgets, forecasting, vendor management, or portfolio analytics

What the JD emphasized

  • highly regulated environments
  • regulated environments
  • GxP expectations
  • inspection readiness
  • regulated industries

Other signals

  • applying AI automation
  • production-grade AI systems
  • regulated environments
  • MLOps
  • scaling AI solutions