Senior Professional, AI & Data Science- AI/ML Engineer

Cargill

Atlanta, GA

Full Time

Senior

6 days ago

Job Description

About the Role

Cargill's size and scale allows us to make a positive impact in the world. Our purpose is to nourish the world in a safe, responsible and sustainable way. We are a family company providing food, ingredients, agricultural solutions and industrial products that are vital for living. We connect farmers with markets so they can prosper. We connect customers with ingredients so they can make meals people love. And we connect families with daily essentials — from eggs to edible oils, salt to skincare, feed to alternative fuel. Our 160,000 colleagues, operating in 70 countries, make essential products that touch billions of lives each day. Join us and reach your higher purpose at Cargill.

Key Responsibilities

Plans and leads the development of artificial intelligence models from design and prototyping through deployed solutions to drive decision making.
Extracts and integrates complex data from various sources, analyzing datasets for bias and applying mitigation strategies.
Reviews complex data sets for exploratory data analysis to identify trends and patterns that inform business strategies.
Develops and deploys artificial intelligence models, including monitoring and evaluating ongoing performance for accuracy, scaling, and deployment.
Establishes software and AI engineering patterns and principles to design, develop, test, integrate, maintain, and troubleshoot complex AI solutions, incorporating security practices.
Documents development and code to support knowledge sharing.
Presents techniques and results to both technical and non-technical audiences.
Examines emerging AI and optimization principles to improve analytical capabilities and deploy models into production.
Works closely with business stakeholders and cross-functional teams to understand needs and develop AI models for digital applications.

Requirements

Minimum of 4 years of relevant work experience.
Typically 5 or more years of relevant experience.
Experience operating production MLOps / LLMOps or GPU-accelerated workloads in AWS for 2+ years.