Principal Applied AI Engineer (Hybrid)
AbbVie
July 01, 2026
Remote friendly (North Chicago, IL)
United States
$124,500 - $236,500 USD yearly
IT
Key Responsibilities:
- Collaborate with cross-functional stakeholders to identify, prioritize, and define opportunities to apply AI and machine learning to operations challenges (e.g., predictive maintenance, process optimization, quality monitoring)
- Map, analyze, and assess current-state business processes to identify inefficiencies and improvement opportunities and inform where AI-enabled solutions can drive value
- Translate operations needs into clear AI/ML problem statements and success metrics
- Partner with data science, engineering, and IT teams to select appropriate algorithms, technologies, and tools and ensure solutions meet business and compliance needs
- Support vendor assessment, selection, and drive prioritized use cases from initial scoping through technical proof of concept
- Partner with automation, robotics, and digital teams to enable intelligent process automation and advanced analytics
- Integrate AI/ML solutions with operations data platforms (MES, SCADA, ERP, IoT) and ensure seamless deployment in production environments
- Establish robust documentation, testing, monitoring, and model management practices (GxP, FDA, data privacy)
- Participate in AI governance, best practice development, and continuous improvement initiatives
- Support change management, training, and knowledge transfer for adoption
- Stay up-to-date with emerging AI/ML and manufacturing digital transformation trends
Qualifications:
- Bachelor’s or Master’s degree in Business, Operations, Computer Science, Data Science, Engineering, or related field (or equivalent practical experience); advanced degree preferred
- 5+ years building and deploying AI/ML solutions in manufacturing, supply chain, or quality
- Strong AI/ML knowledge and experience applying it to operational/business problems; ability to partner with engineering teams
- Experience integrating AI/ML models into operational/IT systems (MES, SCADA, IoT, ERP, cloud)
- Strong problem-solving, project management, and communication skills
- Familiarity with GxP, FDA, and data privacy requirements (plus)
- Collaborate with cross-functional stakeholders to identify, prioritize, and define opportunities to apply AI and machine learning to operations challenges (e.g., predictive maintenance, process optimization, quality monitoring)
- Map, analyze, and assess current-state business processes to identify inefficiencies and improvement opportunities and inform where AI-enabled solutions can drive value
- Translate operations needs into clear AI/ML problem statements and success metrics
- Partner with data science, engineering, and IT teams to select appropriate algorithms, technologies, and tools and ensure solutions meet business and compliance needs
- Support vendor assessment, selection, and drive prioritized use cases from initial scoping through technical proof of concept
- Partner with automation, robotics, and digital teams to enable intelligent process automation and advanced analytics
- Integrate AI/ML solutions with operations data platforms (MES, SCADA, ERP, IoT) and ensure seamless deployment in production environments
- Establish robust documentation, testing, monitoring, and model management practices (GxP, FDA, data privacy)
- Participate in AI governance, best practice development, and continuous improvement initiatives
- Support change management, training, and knowledge transfer for adoption
- Stay up-to-date with emerging AI/ML and manufacturing digital transformation trends
Qualifications:
- Bachelor’s or Master’s degree in Business, Operations, Computer Science, Data Science, Engineering, or related field (or equivalent practical experience); advanced degree preferred
- 5+ years building and deploying AI/ML solutions in manufacturing, supply chain, or quality
- Strong AI/ML knowledge and experience applying it to operational/business problems; ability to partner with engineering teams
- Experience integrating AI/ML models into operational/IT systems (MES, SCADA, IoT, ERP, cloud)
- Strong problem-solving, project management, and communication skills
- Familiarity with GxP, FDA, and data privacy requirements (plus)