Principal for AI and GenAI - AI CoE

UPS

About The Position

We are hiring a Staff AI & GenAI Engineer to join UPS’s ML Innovation and AI Center of Excellence. This is a hands‑on engineering role focused on designing, building, and operating production‑grade AI and GenAI systems at enterprise scale. You will own the end‑to‑end engineering of medium‑ to large‑scale AI solutions—from system architecture and model integration through deployment, performance optimization, and reliability in production. The role requires deep understanding of AI/ML fundamentals, strong software engineering skills, and a proven track record of shipping and operating scalable AI systems across domains such as personalization, memory, diagnostics, representation, and reasoning. As a Staff‑level engineer, you will set technical direction, raise engineering standards, and collaborate closely with platform, product, and applied science teams to turn complex problems into durable, high‑impact solutions. Why this role matters: You will directly shape how AI is engineered, deployed, and scaled across UPS, enabling reliable, real‑world AI capabilities that impact millions of customers and core business operations. Description This role is a deeply technical, hands‑on position. While it operates at Senior Staff scope, it does not involve people management. Success is defined by technical execution, system ownership, and sustained production impact.

Requirements

Strong ML and AI expertise and deep understanding of the ML and AI fundamentals including mathematics, architectures, representation and reasoning, generation/diffusion processes, and diagnostics
Strong Computer Science algorithmic and theory knowledge, and strong statistical fundamentals.
10+ years of experience designing, building, deploying, and maintaining medium to large-scale ai/ml systems in production environments (not just strategic or advisory roles).
5+ Years of experience in at least one domain of application for ML: NLP, Computer Vision, reinforcement learning. A deep understanding of the applications, challenges, and opportunities in these domains.
Ability to distill and formulate a vision and requirements from a vague desiderata description of a project outcome
Excellent leadership and communication skills (verbal and written) with the ability to effectively advocate technical solutions to research scientists, engineering teams as well as business audiences.
Good programming skills in python, java and c, frameworks like Pytorch, Keras, or related high-level languages

Nice To Haves

Demonstrated hands‑on ownership of complex, production AI systems beyond design or oversight
Experience personally leading critical technical execution, not just coordinating teams or projects
Proven ability to debug, optimize, and stabilize large‑scale systems under real production pressure
Track record of driving cross‑team technical outcomes through code, architecture, and operational leadership
Experience operating in environments where reliability, security, and performance directly impact core business operations

Responsibilities

Design, build, deploy, and maintain medium to large production AI/GenAI systems, taking full ownership of engineering, deployment, and operationalization.
Provide technical leadership and mentorship to data scientists and engineers across various teams, fostering a culture of innovation and excellence in AI/GenAI, even without direct managerial authority.
Promotes and evangelizes best practices on data governance, data stewardship, data science, and ethical AI to internal and external customers, acting as a key technology evangelist for AI/GenAI capabilities across the enterprise
Serve as a core member of the AI Center of Excellence, driving AI adoption, setting standards, and providing expert consultation across business units.
Communicates verbally and in writing to business customers and senior leadership team, including regular interaction with the CDTO, CTO, and other C-level executives, educating them about our systems, as well as sharing insights and recommendations.
Provides expertise in the execution of advanced analytics solutions that addresses specific challenges across the organization.
Works with internal and external data science teams to identify appropriate models/algorithms that solve predictive and prescriptive requirements that can be integrated to improve current processes, drive better insights, increase profits, and develop new strategies for products and services.
Identifies and recommends new opportunities to leverage data as a strategic asset to solve business problems.
Identifies, explores, and recommends emerging tools and technologies that will support the acceleration of the data pipelines and the end-to-end data science lifecycle to meet current and future business requirements.
Defines and identifies roadmaps to increase opportunities and efforts that move the organization from descriptive to predictive and prescriptive analytics.
Acts as SME on UPS business processes, data, and advanced analytics capabilities to scope problems, data required to solve problems, model, and available frameworks on predictive and prescriptive analytic solutions internally and in the industry.
Defines strategies that supports the creation, development, and delivery of analytic solutions to meet business needs.
Maintains broad understanding of implementation, integration, and inter-connectivity issues with emerging tools and technologies.