Packaging Artificial Intelligence/Machine Learning Engineer

Caterpillar Inc.•Morton, IL

2d•Onsite

About The Position

Your Work Shapes the World at Caterpillar Inc. 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. At Caterpillar, we work to help our customers build a better world. Without our team of talented, bright and driven individuals, we wouldn’t be the Caterpillar we are today. Now, this is your chance to join our team and do work that matters. 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. Job Summary: 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. Additional Info: This role is located in Morton, IL and does not offer relocation This role requires up to 20% domestic travel

Requirements

Accuracy and Attention to Detail: Understanding the necessity and value of accuracy; ability to complete tasks with high levels of precision.
Analytical Thinking: Knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of organizational problems and create alternative solutions that resolve these problems.
Packaging (AI/ML and Data-Driven Development): Practical knowledge in machine learning, programming, and/or data querying to enhance packaging operations. Key skills include applying ML techniques for business improvements, using Python and/or R for model development, and performing data mining and cleaning for accurate analysis.

Nice To Haves

Business Statistics: Knowledge of the statistical tools, processes, and practices to describe business results in measurable scales; ability to use statistical tools and processes to assist in making business decisions
Machine Learning: Knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services.
Programming Languages: Knowledge of basic concepts and capabilities of programming; ability to use tools, techniques and platforms in order to write and modify programming languages.
Query and Database Access Tools: Knowledge of data management systems; ability to use, support and access facilities for searching, extracting and formatting data for further use.
Requirements Analysis: Knowledge of tools, methods, and techniques of requirement analysis; ability to elicit, analyze and record required business functionality and non-functionality requirements to ensure the success of a system or software development project.
Programming Python, R, JavaScript, Java
ML/AI Frameworks TensorFlow PyTorch Scikit‑learn
Data Tools SQL Spark Pandas
DevOps/MLOps Docker Kubernetes CI/CD Pipelines
Front‑End (for UI Development) React Angular
Cloud Platforms AWS Azure Google Cloud Platform (GCP)

Responsibilities

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.
Data Engineering & Preprocessing 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.
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 TensorFlow, PyTorch, and Scikit‑learn.
Deployment & Integration 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.
Full‑Stack Application Development 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.
Monitoring & Maintenance Tracks and evaluates model performance post‑deployment to ensure stability and accuracy. Implements model retraining strategies, error‑handling mechanisms, and scalability improvements.