Enterprise Applied AI Lead

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At Perrigo, we are driven by our mission to Makes Lives Better Through Trusted Health and Wellness Solutions, Accessible to All
. We are proud to be a Top 10 player in the European Consumer Self-Care market and the largest U.S. store brand provider of over the counter and infant formula. Dedicated to providing The Best Self-Care for Everyone
, we are the people behind the brands you trust. We Are Perrigo. We are committed to enhancing the wellbeing of our colleagues and consumers alike. We pride ourselves on fostering an inclusive, collaborative culture where each person can experience a sense of belonging.

Join us on our One Perrigo journey as we evolve to win in self-care.

This is a strategic leadership role within the Data, Analytics & AI organization, focused on advancing Perrigo’s applied AI capabilities. The Applied AI Lead will be responsible for identifying, developing, and deploying AI solutions that drive business value across functions such as Brand & Category, Commercial, R&D, supply chain, marketing, and finance. This role reports directly to the VP – Data, Analytics & AI and will play a pivotal role in Perrigo’s digital transformation journey.

• Define and execute the applied AI strategy aligned with Perrigo’s business goals.
• Identify high-impact AI use cases and lead cross-functional initiatives to deliver solutions.
• Collaborate with business leaders to prioritize AI projects and measure ROI.
• Define and execute a multi‑year roadmap converging agentic AI, RPA, and process-mining.

• Lead the development and deployment of ML models and AI applications leveraging Gen AI, AI Agents, Agentic AI as well as AI/ML cloud services such as Azure ML.
• Operationalize an Agentic Automation CoE—governing standards, reusable templates, and ROI tracking.
• Ensure scalability, reliability, and ethical use of AI technologies.
• Oversee model lifecycle management including training, validation, monitoring, and retraining.
• Evaluate and implement AI platforms & tools (e.g., Azure ML, Databricks, Hugging Face).
• Architect modular multi‑agent systems powered by frontier LLMs and leading agent frameworks (Lang Chain family, Auto Gen, CrewAI, etc.).
• Drive automation and MLOps practices for efficient model deployment.
• Integrate AI solutions with enterprise systems and data platforms.
• Lead and mentor a team of data scientists, AI/ML engineers and AI Architects.
• Foster a culture of innovation, experimentation, and continuous learning.
• Promote agile methodologies and cross-functional collaboration.

• Ensure responsible AI practices including fairness, transparency, and privacy.
• Collaborate with legal and compliance teams to align AI initiatives with regulations.
• Establish governance frameworks for AI model usage and data handling.

• Technical Expertise:
  Proficiency in Python, Tensor Flow, PyTorch, and cloud-native AI platforms.
• AI/ML Knowledge:
  Strong understanding of supervised, unsupervised, and reinforcement learning.
• Project Management:
  Proven ability to lead complex AI initiatives and deliver results.
• Communication:
  Excellent verbal and written communication skills, with the ability to influence stakeholders.
  
  Leadership:
  Demonstrated success in building and leading high-performing AI teams.
• Problem Solving:
  Strong analytical mindset with a focus on scalable solutions.
• These skills are typically acquired through the completion of a Bachelor's degree in computer science, data science, or closely related field; combined with 10–15 years of experience in AI/ML, with at least 3 years in a leadership role.
• 7+ years hands‑on with Python, SQL, R, MATLAB, PyTorch, Keras, Git.
• 10+ years architecting ML/deep‑learning solutions incl. LLMs (GPT‑4, BERT, LLaMA, Dolly) and RAG pipelines.
• 8+ years building web apps (Dash, Streamlit, Shiny) and advanced data products.
• 8+ years implementing scalable AI/ML on platforms like Databricks with strong AI/MLOps. Deep knowledge of cloud data platforms (AWS, Azure) and compliance (GxP, HIPAA, GDPR)
• Masters of PhD preferred.

We believe our…