AI Embedded Systems Engineer

Pfizer Pfizer · Pharma · Washington – Bothell, United States, United States

This role focuses on developing software and data solutions to enable AI adoption in Pharmaceutical Sciences by automating, digitizing, and contextualizing scientific datasets. The engineer will partner with scientists, develop data products and pipelines for AI/ML use cases, and work with automation teams. Experience with data handling, integration, analysis, SQL, cloud data warehouses, and systems programming languages is required.

What you'd actually do

  1. Development of data products and custom applications to support downstream AI/ML use cases, automation, and data contextualization.
  2. Development of data analysis and system integration pipelines.
  3. Work with robotics and automation teams to understand data needs and partner with other developers.
  4. Implementation, testing, and validation of new methods for data analysis and visualization techniques
  5. Partner with scientists to understand systems and requirements related to data capture, analysis, and reporting including digitization of current paper-based processes.

Skills

Required

  • BS in Biology, Chemistry, Physics, Statistics, Computer Sciences or a related technical discipline with 4+ years of experience in a software development role focused on embedded systems and/or data operations
  • Master’s degree and 2+ years of experience in a software development role focused on embedded systems and/or data operations
  • Recent PhD graduate in a related technical discipline.
  • Experience with data handling, integration and analysis
  • Strong experience with SQL and cloud data warehouses
  • Experience developing data products and data integration solutions in a research or industry environment
  • Experience solving complex analyses/problems in a timely fashion
  • Exceptional programming skills in at least one systems language (e.g., C, C#, Java, Go) and python.
  • Strong communication skills—verbal, written, and presentation

Nice to have

  • Proven expertise in software engineering, package development, cloud architectures, CI/CD and software engineering tooling
  • Familiarity with pertinent libraries within the scientific Python stack
  • Experience with Github Copilot or other AI-enabled coding tools that accelerate solution delivery.
  • Experience taking ideas from prototype to production
  • Experience in regulated industry & software validation practices

What the JD emphasized

  • GMP compliance
  • regulated industry & software validation practices

Other signals

  • Develops data products and custom applications to support downstream AI/ML use cases
  • Works with robotics and automation teams to understand data needs
  • Implementation, testing, and validation of new methods for data analysis and visualization techniques