Global AI Engineer

Life changing therapies. Global impact. Bridge to thousands of biopharma companies and their patients.

We are PCI.

Our investment is in People who make an impact, drive progress and create a better tomorrow. Our strategy includes building teams across our global network to pioneer and shape the future of PCI.

The AI Engineer will be responsible for developing, implementing, and maintaining AI-driven solutions to enhance the efficiency, accuracy, and scalability of our pharmaceutical packaging operations. This role will involve collaborating with cross‑functional teams, including operations, quality assurance, and regulatory compliance, to integrate AI technologies into our workflows. The ideal candidate will have a strong background in AI/ML, experience in regulated industries, and a passion for leveraging technology to solve complex operational challenges.

• Design and develop AI/ML models to optimize packaging processes, such as automated quality control, defect detection, inventory management, and predictive maintenance for packaging equipment.
• Design AI tools for real‑time monitoring of production lines to ensure compliance with Good Manufacturing Practices (GMP) and other regulatory standards.
• Create algorithms to improve demand forecasting, supply chain logistics, and resource allocation.
• Deploy and integrate AI models into production environments, ensuring seamless integration with existing packaging systems, IoT devices, and enterprise software.
• Collaborate with IT and engineering teams to integrate AI solutions with manufacturing execution systems (MES) and enterprise resource planning (ERP) platforms.
• Ensure scalability and robustness of AI tools to handle high‑throughput packaging operations.
• Maintain and optimize AI systems to ensure consistent performance, reliability, and compliance with pharmaceutical regulations (e.g., FDA, EMA).
• Continuously improve AI models by analyzing performance metrics, retraining models with new data, and incorporating feedback from operations teams.
• Troubleshoot and resolve issues related to AI tool performance or integration.
• Collaborate and ensure compliance – work closely with quality assurance and regulatory teams to ensure AI solutions meet stringent industry standards and validation requirements.
• Partner with operations teams to identify pain points and opportunities for AI‑driven process improvements.
• Document AI system designs, processes, and validation protocols to support audits and regulatory submissions.
• Innovate and research – stay updated on advancements in AI/ML, particularly in applications for manufacturing and pharmaceuticals.
• Explore emerging technologies (e.g., computer vision, NLP, reinforcement learning) to enhance packaging operations.
• Propose and prototype new AI‑driven solutions to address evolving business needs.
• Maintain knowledge of and adherence to all PCI, cGMP, and GCP policies, procedures, rules.
• Perform job duties as assigned by Manager/Supervisor.

Carrying out supervisory responsibilities in accordance with the organization’s policies and applicable laws. Responsibilities include interviewing, hiring, and training employees; planning, assigning, and directing work; appraising performance; rewarding and disciplining employees; addressing complaints and resolving problems. Independent and creative engineer, strong innovation and problem‑solving skills, no direct personnel supervision. Liaison with key stakeholders across the organization to realize successful outcomes.

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field. A PhD is a plus.
• Up to 3+ years of experience in designing, developing, and deploying AI/ML models in a production environment.
• Proficiency in Python, R, or similar programming languages for AI/ML development.
• Experience with ML frameworks and libraries (e.g., Tensor Flow, PyTorch, Scikit‑learn).
• Knowledge of computer vision, time‑series analysis, or predictive modelling techniques.
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) for…