Packaging Artificial Intelligence​/Machine Learning Engineer

Career Area

Supply Chain and Logistics

When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live.

Together, we are building a better world, so we can all enjoy living in it.

We want you to help us enable customer success, make progress possible around the world and help our communities grow and thrive. We are looking for a dynamic, organized self-starter to join our Product Support and Logistics Division as a Packaging AI/ML Engineer in Morton, IL.

Our Product Support and Logistics Division (PSLD) is one of the most innovative divisions within Caterpillar. In PSLD, as within all of Caterpillar, our priority is our customers and helping them build a better world. PSLD is responsible for the worldwide distribution of Cat aftermarket parts, integrated logistics, and global service to develop and support our global dealer network and customers.

We’re committed to our customers, who build a better world with our products, services and solutions. We understand and show the value of why they should always choose us. We’re exploring new ideas and opportunities – innovating to discover the breakthroughs necessary for tomorrow’s growth.

• The Packaging AI/ML (Artificial Intelligence/Machine Learning) Engineer performs analytical tasks and initiatives on huge amounts of data to support data‑driven business decisions and development. Utilizes AI/ML technologies to enhance packaging engineering processes, automation, quality, and operational efficiency.

• This role is located in Morton, IL and does not offer relocation.
• This role requires up to 20% domestic travel.

• Directing the data gathering, data mining, and data processing processes in huge volume; creating appropriate data models.
• Exploring, promoting, and implementing semantic data capabilities through Natural Language Processing, text analysis and machine learning techniques.
• Leading to define requirements and scope of data analyses; presenting and reporting possible business insights to management using data visualization technologies.
• Conducting research on data model optimization and algorithms to improve effectiveness and accuracy on data analyses.
• Additionally, proficiency in query and database tools is essential for creating and testing queries, connecting to data warehouses, and analyzing results. Familiarity with advanced query features like sorting, filtering, and basic calculations ensures effective data handling.
• The role also involves implementing and supporting programming languages, writing and reviewing code, and following organizational standards for structured programming.

• Collects, cleans, and transforms raw data into usable formats for packaging‑related AI/ML applications.
• Builds pipelines for data ingestion and feature engineering to support scalable model development.

• Designs, trains, and optimizes machine learning or deep learning models relevant to packaging, such as defect detection, quality prediction, optimization modeling, or sustainability assessments.
• Experiments with algorithms and frameworks such as Tensor Flow, PyTorch, and Scikit‑learn.

• Packages models into APIs or microservices for seamless integration with packaging systems or business platforms.
• Deploys AI/ML models into cloud, edge, or on‑premises environments to support real‑time packaging line insights and automation.

• Builds user interfaces or dashboards for visualizing AI outputs or interacting with deployed models.
• Handles backend logic and integrates AI services with core packaging engineering or business applications.

• Tracks and evaluates model performance post‑deployment to ensure stability and accuracy.
• Implements model retraining…