Job Summary

The SVP Artificial Intelligence is a strategic executive leader responsible for shaping the vision, building the roadmap, and driving the execution of AI and Machine Learning (ML) strategies that transform Medline enterprise products, services, and operations. This role ensures alignment with senior leaders, engineers, product teams, and external partners to scale real-world AI solutions responsibly and efficiently.

Job Description

MAJOR RESPONSIBILITIES

Strategic Leadership & Vision

• Develop and own the enterprise AI strategy aligned with business objectives, innovation goals, and customer impact.
• Lead cross functional AI initiatives, collaborating with engineering, product, data, security, operations, marketing, and legal teams.
• Identify and evaluate emerging AI technologies for integration into products or internal operations.
• Represent the AI function to senior leadership and board, presenting clear metrics, progress reports, and strategic opportunities.

AI Innovation & Technology Direction

• Drive innovation through advanced AI and ML applications, including natural language processing (NLP), computer vision, generative AI, and predictive modeling.
• Oversee the full machine learning lifecycle, from model to development, training, and testing to deployment, monitoring, and retraining.
• Define AI success metrics, time-to-value, accuracy, adoption rates, business ROI, and track performance.
• Foster a culture of experimentation and innovation, encouraging agile delivery and continuous learning.

Operational Excellence & ML Operations

• Establish and enforce ML operations best practices to support scalable and maintainable AI pipelines.
• Manage AI program budgets, resource allocation, vendor negotiations, and technology investments.

AI Governance, Ethics, & Compliance

• Define and manage AI governance frameworks, ensuring models are explainable, fair, ethical, and compliant with regulations.
• Promote responsible AI practices, leading efforts on bias mitigation, model transparency, and stakeholder education.
• Ensure secure and ethical data use, partnering with InfoSec and legal to govern training data sources, privacy protocols, and risk assessments.

Talent, Culture and Ecosystem Leadership

• Shape and lead AI talent strategy, including recruitment, professional development, and succession planning for AI teams.
• Lead partnerships with academia, AI research institutions, and strategic technology vendors to stay ahead of the innovation curve.

 

MINIMUM JOB REQUIREMENTS

Education

Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

Certification / Licensure

n/a

Work Experience

• 10+ Years experience in AI/ML including 5+ years in leadership roles.
• Proven track record of delivering production-ready AI/ML systems at scale.
• Deep expertise in Python, ML frameworks (TensorFlow, PyTorch), cloud AI (AWS, GCP, Azure), and distributed systems.
• Experience managing complex AI projects across multiple business functions.
• Deep understanding of responsible AI, algorithmic fairness, and data ethics.

Knowledge / Skills / Abilities

• Advanced AI/ML concepts: deep learning, reinforcement learning, NLP, computer vision, generative AI and time series modeling.
• Model lifecycle management: training, validation, monitoring, retraining, and decommissioning.
• ML operations practices: CI/CD pipelines for ML, model versioning, drift detection, and reproducibility.
• Cloud infrastructure and tools: AWS SageMaker, GCP Vertez AI, Azure ML Studio, Kubernetes, Docker.
• AI ethics and governance frameworks: bias mitigation, explainability and fairness.
• Enterprise data architecture: big data platforms (Spark, Hadoop), data lakes, feature stores, and data warehouses.
• Relevant regulations and standards: GDPR, CCPA, HIPPA, ISO/IEC standards for AI.
• Business strategy and industry knowledge to align AI initiatives with commercial outcomes.

PREFERRED JOB REQUIREMENTS

Education

Ph.D. degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

Certification / Licensure

Stanford University’s Machine Learning

Deep Learning Specialization

Microsoft certified: Azure engineering associate

AWS Certified Machine Learning Specialty

Certified Analytics Professional (CAP)

PMP Certification

Work Experience

Experience in healthcare manufacturing regulated industries.

Familiarity with generative AI, large language models (LLMs) and foundation model deployment.

Published work, patents, or active contributions to open-source AI initiatives.

Experience in executive communication with the ability to translate technical concepts to non-technical stakeholders.

Medline Industries, LP, and its subsidiaries, offer a competitive total rewards package, continuing education & training, and tremendous potential with a growing worldwide organization.

The anticipated salary range for this position:

$355,000.00 - $533,000.00 Annual

The actual salary will vary based on applicant’s location, education, experience, skills, and abilities. This role is bonus and/or incentive eligible. Medline will not pay less than the applicable minimum wage or salary threshold.

Our benefit package includes health insurance, life and disability, 401(k) contributions, paid time off, etc., for employees working 30 or more hours per week on average. For a more comprehensive list of our benefits please click here. For roles where employees work less than 30 hours per week, benefits include 401(k) contributions as well as access to the Employee Assistance Program, Employee Resource Groups and the Employee Service Corp.

We’re dedicated to creating a Medline where everyone feels they belong and can grow their career. We strive to do this by seeking diversity in all forms, acting inclusively, and ensuring that people have tools and resources to perform at their best. Explore our Belonging page here.

Medline Industries, LP is an equal opportunity employer. Medline evaluates qualified individuals without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, age, disability, neurodivergence, protected veteran status, marital or family status, caregiver responsibilities, genetic information, or any other characteristic protected by applicable federal, state, or local laws.