Applied AI and Simulation Engineer (Packaging Engineering)
DellAustin, Texas, United StatesPosted 27 March 2026
Job Description
Applied AI and Simulation Engineer (Packaging Engineering)
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
Take the first step towards your dream career
Every Dell Technologies team member brings something unique to the table.
Here’s
what we are looking for with this role:
Essential Requirements
• Bachelor's or
master's degree in
M echanical 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 and handling noisy, sparse, and real -world datasets.
•
Experience with: Machine
L earning 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 , performance evaluation,
and engineering analysis methods.
Desirable Requirements
• Experience in mechanical engineering, packaging engineering,
theoretical and applied mechanics,
or manufacturing environments | Familiarity with design optimization, DOE, or statistical modeling |
Experience in building data pipelines or ML workflows in production| Fami liarity with hybrid modeling simulation (simulation ML | Exposure to sustainability initiatives such as material reduction or lifecycle analysis
• Experience
working with cross-functional, global teams.
Compensation
Dell is committed to fair and
equitable
compensation practices. The salary range for this role is $ 144,500
– $187.000 .
Benefits and Perks of working at Dell Technologies
Your life. Your health. Supported by your benefits. You can explore the overall benefits experience that awaits you as a Dell Technologies team member — right now at MyWellatDell.com
Who we are
We believe that each of us has the power to make an impact.
That’s
why we put our team members
at
the center of everything we do. If
you’re
looking for an opportunity to grow your career with some of ... (truncated, view full listing at source)
Apply Now
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