About the Role
The Vice President of Artificial Intelligence (AI) and Machine Learning (ML) leads the vision and global strategic direction for AI/ML across the enterprise. Drawing on deep experience and strong partnerships with industry experts, business leaders, and technology stakeholders, this role drives measurable business and customer value through the application of AI, GenAI, Agentic AI, and machine learning solutions. The Vice President collaborates across functions to understand complex organizational challenges, reframe problem statements, and design multi-stage, data-driven solutions embedded in software. Success in this role requires the ability to influence decision-making through return-on-investment analysis, compelling data storytelling, and visualization techniques that accelerate adoption and impact.
At UPS, we’re not just delivering packages—we’re delivering innovation at scale. As a Vice President of AI/ML, you’ll lead transformative work that touches every corner of our global network. You’ll have the opportunity to shape enterprise-wide AI strategy, partner with visionary leaders, and deploy cutting-edge technologies like GenAI and agentic systems. With executive sponsorship, a culture that values experimentation, and a clear mandate to drive measurable business impact, this is your chance to lead with purpose and move our world forward, by delivering what matters.
Responsibilities
Strategy and Leadership
- Leads strategy development and execution of industry-leading AI and GenAI capabilities, processes, organization, systems, and talent development within the Data Science and AI Software Engineering teams.
- Works with leaders across the enterprise to drive technology transformation to optimize domestic/global go-to-market launch planning strategies through innovative and highly strategic decisions and investments in AI/ML/GenAI/Agentic.
- Leads a team of Directors who oversee data scientists, ML engineers, and AI product managers across multiple domains. Provides strategic direction, mentorship, and executive sponsorship to ensure alignment with enterprise goals and delivery of high-impact AI/ML/GenAI/Agentic solutions.
- Develops and oversees the AI vision and adoption among federated analytics/AI departments across the organization and advocates a data-driven culture that rapidly drives business and customer value by leveraging AI/ML/GenAI/Agentic AI techniques.
- Develops multi-year roadmaps and strategies to meet goals of maturity in data and AI governance, Enterprise and Functional Analytics, and data and AI fluency to support the acceleration and delivery of advanced analytic solutions to meet business needs; drives focus on technology, automation, productivity, and quality of service.
- Articulates business vision and strategy and mobilizes the workforce to collaboratively reach evolving business objectives through internal and external relationships.
- Champions technology and funding recommendations to senior management to ensure technology and value are maximized and meet business objectives.
- Assesses the financial implications and business case for AI/ML/GenAI/Agentic AI investments and helps communicate overarching return on investment, business value drivers, success metrics, etc.
- Provides thought leadership on AI/ML/GenAI/Agentic AI methods, algorithms/model development, validation, tools, etc.
AI/ML Development and Implementation
- Develops Artificial Intelligence/Machine Learning (AI/ML) models and solutions that will provide key insights on our pipeline assets to drive global commercial strategies and create a competitive advantage by making better business decisions derived through strategic AI approaches.
- Embeds AI in application development leveraging a product-centric approach.
- Leads the development of cutting-edge methodologies in areas such as predictive and prescriptive modeling, time-series and causal inference, graph ML and network science, natural language processing and LLM fine-tuning, generative and agentic AI systems, and operations research (optimization & simulation).
- Determines the key competencies, processes, organization, and systems required to build an industry-leading AI/ML/GenAI/Agentic AI capability.
- Define and track success metrics such as model adoption, business value delivered, and time-to-insight acceleration.
Cross-Functional Collaboration
- Partners with functional teams to develop a cross-functional product roadmap for data science, ML, predictive AI, GenAI, Agentic AI.
- Partners with legal, compliance, and governance teams to ensure responsible AI development, including bias mitigation, explainability, and adherence to UPS’s AI guardrails.
- Interfaces externally with domestic/global areas in the development of the AI/ML/GenAI/Agentic AI strategy and guidelines for insight generation and usage.
- Communicates verbally and in writing to business customers and senior leadership team with various levels of technical knowledge, educates them about our systems, and shares insights and recommendations that inform business strategies.
- Develops and participates in the organization’s Data and AI Communities of Practice.
Qualifications
Technical Expertise
- Strong understanding of AI algorithms development processes, trade-offs, and limitations.
- Deep expertise in data science, machine learning, statistical modeling, and AI platform technologies.
- Extensive experience with modern AI frameworks, AI/XOps tools, and cloud platforms (e.g., AWS, GCP, Azure).
- Deep understanding of generative and agentic AI technologies.
- Advanced knowledge of workflow tools, automation systems, and compliance frameworks is a plus.
- Experience leading and overseeing enterprise advanced analytics projects in production at scale and implementing open-source or vendor products with or without the use of enterprise analytics/AI platforms.
- Demonstrated ability to effectively advocate strategic direction around technical solutions to data science professionals, data engineering teams, and business audiences.
Analytical And Problem-Solving Skills
- Superior analytical skills with high attention to detail and accuracy with the ability to identify AI lifecycle bottlenecks and requirements for platforms and tools.
- Demonstrated experience driving results with data analytics and problem formulation techniques.
- Strong business acumen with the ability to align data science initiatives to strategic and operational goals.
Project and Product Management
- Experience managing complex projects in a fast-paced business and technology environment.
- Experience leading/working with product management teams in an agile environment.
- Experience developing product specs, writing user stories, and identifying and prioritizing competing products to deliver results while making sense of ambiguity.