Control Systems Engineering Intern

Change the world. Love your job.

As a Controls Systems Engineering intern youll help architect and develop control systems that enable TIs supply chain operations to set stable competitive lead times while preserving optimal semiconductor manufacturing. Youll gain hands-on experience with system architecture control theory modeling simulation and data analytics to drive efficient manufacturing processes. And youll have the opportunity to work in exciting areas like digital twin modeling discrete event simulation machine learning optimization automated control systems supply chain logistics and semiconductor manufacturing process control.

Some of your responsibilities will include but will not be limited to:

Assisting in the design of control systems and algorithms for high-mix semiconductor manufacturing and supply chain logistics

Supporting discrete event simulation platforms and contributing to system performance modeling

Participating in the application of statistical modeling and optimization techniques to improve system stability

Helping translate requirements into architecture diagrams configuration logic and data models

Contributing to systems-of-systems interoperability through verification planning and testing

Assisting in the development and maintenance of control software with automated testing

Supporting debugging of hardware-software interactions using instrumentation and data logging

Contributing to the automation of recurring engineering tasks to improve efficiency

Participating in digital twin modeling and real-time data synchronization projects

Learning about advanced control algorithms and predictive control capabilities

Put your talent to work with us as a Controls Systems Engineering Intern!

Texas Instruments will not sponsor job applicants for visas or work authorization for this position.

Minimum requirements:

Currently pursuing an undergraduate or graduate degree in Electrical/Computer Engineering Computer Science Mathematics Operations Research Industrial/Systems Engineering Data Science or related field

Cumulative 3.0/4.0 GPA or higher

Preferred qualifications:

Coursework or project experience with control systems signal processing or system dynamics

Programming experience with Python C++ Java or similar object-oriented languages

Exposure to statistical modeling optimization techniques or simulation tools through coursework or projects

Basic understanding of mathematical concepts including linear algebra calculus and probability

Experience with data analysis tools or frameworks (NumPy Pandas MATLAB or similar)

Familiarity with control theory concepts such as closed-loop control PID control or feedback systems

Exposure to simulation platforms or modeling tools through academic projects

Experience with data serialization formats (JSON YAML XML) or configuration management

Knowledge of machine learning concepts or AI/ML applications in engineering

Understanding of semiconductor manufacturing processes or supply chain concepts

Ability to establish strong relationships with key stakeholders critical to success both internally and externally

Strong verbal and written communication skills

Ability to quickly ramp on new systems and processes

Demonstrated strong interpersonal analytical and problem-solving skills

Ability to work in teams and collaborate effectively with people in different functions

Ability to take the initiative and drive for results

Strong time management skills that enable on-time project delivery

Efficiency instinct to automate recurring tasks and improve processes