At Dell Technologies, we create technologies that drive human progress. Our Packaging Engineering team plays a critical role in delivering sustainable, high-performance solutions that protect our products and enhance customer experience. We are looking for an Applied AI and Simulation Engineer to help us transform packaging by focusing on the intersection of AI, physics-based simulation, and machine learning for next generation packaging solutions. This role will drive innovation in design optimization, material performance, and manufacturing efficiency using both data-driven and simulation-based approaches. Join us to do the best work of your career and make a profound impact as an Applied AI and Simulation Engineer on our Packaging Engineering team in Austin.

What You’ll Achieve

As an Applied AI and Simulation Engineer (Packaging Engineering), you will contribute to the development of next generation packaging by combining data-driven intelligence with physics-based modeling. You will work cross-functionally to improve packaging performance, reduce environmental impact, and accelerate innovation.

You will:

• Apply AI techniques and machine learning to optimize packaging design, material usage, and reliability.
• Perform advanced simulations using tools such as Creo to evaluate structural and dynamic performance.
• Develop hybrid models that integrate simulation data with machine learning predictions.
• Build and manage engineering data pipelines and databases for simulation results, and testing data material properties.
• Partner with global teams across engineering, manufacturing, and supply-chain to drive data-informed decisions.
• Analyze physical test data (drop, vibration, compression) and improve correlation with simulation outputs.
• Contribute to automation and scalability of packaging design workflows.

Essential Requirements

• Bachelor's or master's degree in Mechanical engineering, Materials Science, Computer Science, Theoretical and Applied Mechanics, Packaging Engineering, or related field.
• 3-6 years of relevant experience in engineering, simulation, machine learning applications, and developing engineering data platforms from structured and unstructured data handling noisy, sparse, real-world datasets.
• Experience with:
• Machine Learning frameworks (e.g., TensorFlow, PyTorch)
• Simulation Tools, particularly Creo
• Programming in Python
• Knowledge of databases and data management systems (SQL/NoSQL)
• Understanding material behavior, structural analysis, model validation,...