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Pfizer is a global pharmaceutical company focused on developing and providing medicines and healthcare services that support health throughout life. Its work spans scientific innovation and access to safe, effective, and affordable treatments, with a particular emphasis on advancing therapies for cancer and other significant health conditions. The company’s profile may be relevant to professionals exploring careers in pharmaceutical research, healthcare, and related commercial functions.
Senior Scientist, AI Development and Agentic Systems
Develop agentic AI systems and process models for Pfizer’s pharmaceutical manufacturing network. Deliver validated solutions for monitoring, investigations, and engineering decision support.
Description
- Own technical delivery for high-impact projects that combine process expertise with artificial intelligence
- Guide technical work from opportunity definition through validated deployment
- Design, build, and deploy agentic AI systems using LLM agents, tool integration, retrieval, and multi-step reasoning
- Support manufacturing investigations, root cause analysis, batch reviews, and engineering decisions
- Develop mechanistic, hybrid, and machine learning models for chemical and biological processes
- Support GMP applications including soft sensors, real-time monitoring, golden-batch analysis, and advanced process control
- Establish test sets, benchmarks, guardrails, and monitoring practices for regulated AI systems
- Find high-value opportunities for advanced analytics, advanced process control, and AI across the manufacturing network
- Apply engineering principles and experimental data from laboratory, pilot, and commercial equipment
Requirements
- Master’s degree in engineering, applied mathematics, or computer science; a Ph.D. is advantageous
- Expert proficiency in Python
- Experience with modern version control, environment management, testing, and continuous integration tools
- Demonstrated success applying data science and machine learning to real-world, imperfect datasets
- Working knowledge of chemical or biological process fundamentals
- Ability to collaborate across diverse, cross-functional, and geographically distributed teams
- Strong written and verbal communication skills
- Self-directed approach to solving ambiguous problems
- Fluency in both French and English
- Advanced spoken and written English is required
- Experience engineering structured time-series and unstructured data
- Experience developing large language model applications
- Production experience evaluating agent performance and reliability
- Expertise in deep learning and multivariate latent-variable methods
- Cloud development and MLOps experience with AWS, Azure, or an equivalent platform
- Experience with Snowflake and SQL
- Familiarity with process historians, OPC UA, real-time protocols, DeltaV, or comparable distributed control systems
- Familiarity with pharmaceutical manufacturing, GMP data integrity, computer system validation, and AI regulatory guidance
Benefits
- Flexible working model
- Support for work-life balance
- Remote work from off-site locations when appropriate for business needs
- Blended on-site and remote work arrangements
- Accessible candidate experience with accommodations available throughout recruitment
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