Pfizer
Pfizer
Pfizer ir globāls farmācijas uzņēmums, kas koncentrējas uz tādu zāļu un veselības aprūpes pakalpojumu izstrādi un nodrošināšanu, kuri palīdz uzturēt veselību visa mūža garumā. Uzņēmuma darbība aptver zinātniskās inovācijas un drošu, efektīvu un pieejamu ārstēšanas iespēju pieejamības veicināšanu, īpašu uzmanību pievēršot terapiju attīstībai vēža un citu nozīmīgu veselības traucējumu ārstēšanai. Uzņēmuma darbība var būt saistoša speciālistiem, kuri apsver karjeru farmācijas pētniecībā, veselības aprūpē un ar to saistītajās komercfunkcijās.

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.

Apraksts

  • 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

Prasības

  • 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

Priekšrocības

  • 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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