AI/ML Engineer ​

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.

Job Purpose and Impact

• The Senior Professional, AI & Data Science job plans and leads the development of artificial intelligence models from design and prototyping through deployed solutions to drive decision making. With minimal supervision, this role extracts and integrates complex data from various sources, builds advanced models suitable for the business use case and evaluates model performance for accuracy, scaling and deployment. This job also develops compelling and clear communication materials to facilitate partner on board.

• DATA PREPARATION MANAGEMENT: Conducts extraction and integration of complex data from different data sources, analyses the ways in which datasets may be biased and applies mitigation strategies.
• DATA ANALYSIS: Reviews complex data sets for exploratory data analysis to identify trends and patterns that inform business strategies across various areas.
• MODEL DEVELOPMENT: Develops and deploys artificial intelligence models, including monitoring and evaluating ongoing performance to solve complex business problems and derive actionable insights.
• AI ENGINEERING: Establishes software and artificial intelligence engineering patterns and principles to design, develop, test, integrate, maintain and troubleshoot complex and varied generative artificial intelligence software solutions and incorporates security practices in newly developed and maintained applications. .
• DOCUMENT & REPORTING: Documents development and code in ways that allow for support and knowledge sharing.
• COMMUNICATION: Presents techniques and results to technical and non-technical audiences.
• CONTINUOUS LEARNING: Examines existing and emerging artificial intelligence and optimization principles, theories, and techniques to develop and deploy artificial intelligence models into production, improving the organization's analytical capabilities.
• STAKEHOLDER MANAGEMENT: Works closely with businesses to understand needs, and collaborates with cross functional teams to develop artificial intelligence models for digital applications.

• Minimum requirement of 4 years of relevant work experience. Typically reflects 5 years or more of relevant experience.

• Typical: 5-8 years total, including 2 + years operating production MLOps/LLMOps or GPU-accelerated workloads in AWS.