Operations Research Engineer

Intel•Chandler, AZ

10d•Onsite

About The Position

As a Software Research Engineer/Scientist, you will apply your expertise in software development and modeling to solve critical engineering challenges and innovate for the future. Your day-to-day work will involve developing strategic software applications and solutions, as well as conducting research to define boundaries, prototype new ideas, and address customer and technology issues. Your contributions will play a vital role in driving advancements in technology and shaping long-term solutions. This position is part of Intel's Factory Automation organization, which focuses on solving complex challenges to drive innovation and enable future technologies. The team leverages deep technical expertise and in collaboration with Intel Foundry customers, providing provides cutting-edge tools to support Intel's broader mission of delivering world-class products and solutions.

Requirements

Degree in Industrial, Systems, Operations Research Engineering or Equivalent
Bachelor's degree in a relevant field with 4+ years of hands-on experience in software development, modeling, or a Master's degree in a relevant field with 2+ years of experience.
Strong understanding of software modeling and discrete event simulation modeling
Expertise in factory physics, manufacturing science, and stochastic systems.
Proficiency in programming languages such as Python and SQL.
Experience with statistical data analysis tools including JMP and Excel.

Nice To Haves

Discrete event simulation tools such as Automod or FlexSim
Demonstrated ability to collaborate within cross-functional teams and adapt to dynamic environments.
A creative mindset for developing innovative solutions and advancing research methodologies.
Strong communication skills to effectively share insights and findings with technical and non-technical stakeholders.

Responsibilities

Perform modeling analyses to develop solutions to advance Intel's Manufacturing roadmap.
Collaborate with cross-functional teams and industry partners to address critical technology challenges.
Create prototypes and proof-of-concepts to validate ideas and explore new software methodologies and hardware capabilities.
Utilize programming languages and software modeling techniques to solve complex engineering problems.
Apply statistical data analysis and characterization tools to appropriately interpret modeling results and to enhance problem-solving capabilities.
Understanding of numerical issues (scaling, tolerances, infeasibility, warm starts) and modeling tradeoffs: accuracy vs speed, and model decomposition approaches.