Principal for AI and GenAI – AI Center of Excellence – Coe
| Company | United Parcel Service (UPS) |
|---|---|
| Location | Newark, NJ, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Master’s, PhD |
| Experience Level | Expert or higher |
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 experience on training, evaluating, and characterizing ML models and end to end systems
- 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
Responsibilities
- 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.
Preferred Qualifications
- Proven leadership in shipping/designing ML and AI products.
- Experience with cross-functional projects, including de-risking and scoping.
- Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic data-driven enterprise.
- Strong understanding of end-to-end systems with knowledge on cloud architecture, networking and information security
- Hands-on experience launching enterprise advanced analytics projects in production at scale using available Cloud-AI technologies and infrastructures, implementing open-source or vendor products with or without the use of enterprise data and analytical platforms.
- Involvement in the scientific community via publications, collaborations and contributions to industry groups, academia and opensource community.
- Master’s or PhD Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience.