AI Solutions Engineering Intern

Change the world. Love your job.

As an AI Solutions Engineering intern youll help design and build AI-enabled solutions for discriminative and generative applications using a combination of classical and neural network-based machine learning algorithms. Youll gain hands-on experience with cutting-edge AI technologies from developing data pipelines to working with the latest LLMs and neural networks.

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

Assisting in the design and development of AI-enabled solutions using classical and neural network (MLPs RNNs CNNs transformers) based machine learning algorithms

Supporting the creation of efficient data pipelines and contributing to the development of AI agents using LLMs

Participating in testing and monitoring AI model deployments for accuracy and performance

Collaborating with partners across TI to address applications in design (software digital analog) manufacturing (process development fabrication testing) sales (pricing recommendations) and general productivity

Contributing to the development of robust scalable and secure AI solutions

Assisting with model training evaluation and optimization processes

Supporting documentation and analysis of AI solution performance and outcomes

Learning about emerging AI technologies and contributing to solution improvements

Participating in technical reviews and presenting findings to project teams

Put your talent to work with us as an AI Solutions 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 Engineering Computer Engineering Computer Science or a related technical field

Cumulative 3.0/4.0 GPA or higher

Preferred qualifications:

Coursework or project experience with AI/ML concepts and neural networks (MLPs RNNs CNNs transformers)

Programming experience with Python and familiarity with ML frameworks like PyTorch or TensorFlow

Exposure to traditional ML techniques (clustering regression decision trees) through coursework or projects

Basic understanding of mathematical concepts including linear algebra probability and calculus

Experience with SQL programming or database concepts

Exposure to AI/ML applications in areas like natural language processing computer vision or time series analysis

Experience with C/C programming

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

The ability to dream what could be and the drive to make the dream a reality