Senior AI Architect, Data Science & Supply Chain

General Mills Services, Inc.; United States; On-site; USD 150,000 - 249,000; Full time

Job summary

General Mills seeks a Principal Data Scientist to architect enterprise AI platforms and drive end-to-end AI solutions for supply chain optimization. You will collaborate with product, engineering, and data science leaders to frame complex business problems into robust AI systems and governance processes.

Responsibilities include leading LLM/NLP/vision initiatives, mentoring data scientists, and ensuring scalable, secure, and responsible AI adoption across the enterprise.

Qualifications

• 10+ years in data science / analytics with end-to-end delivery
• Advanced degree in a quantitative field
• Strong data science and ML/optimization expertise
• Hands-on experience deploying AI/ML on a major cloud platform
• Proven leadership and mentorship of data scientists
• Experience with unstructured data and AI (LLMs, NLP, CV)
• Excellent communication with technical and non-technical stakeholders
• Proficiency with MLOps concepts and CI/CD for models

Responsibilities

• Lead end-to-end AI solutions focused on Supply Chain decisioning
• Define and deliver production-grade AI/ML products and services
• Architect and govern LLMs, NLP, and computer vision solutions
• Provide technical leadership and set architectural standards
• Ensure governance, privacy, and responsible AI practices
• Mentor data scientists and drive collaboration across teams

Skills

Leadership

Communication

ML deployment

NLP

Optimization

Data science

Mentoring

Education

Advanced degree in quantitative field

Tools

CI/CD for models

Git

GCP

Model monitoring

Job description

General Mills seeks a Principal Data Scientist to architect enterprise AI platforms and drive end-to-end AI solutions for supply chain optimization. You will collaborate with product, engineering, and data science leaders to frame complex business problems into robust AI systems and governance processes.

Responsibilities include leading LLM/NLP/vision initiatives, mentoring data scientists, and ensuring scalable, secure, and responsible AI adoption across the enterprise.