AI Solutions Engineering Intern
Texas Instruments
AI Solutions Engineering Intern
Change the world. Love your job.
As an AI Solutions Engineering intern, you'll help design and build AI-enabled solutions for discriminative and generative applications using a combination of classical and neural network-based machine learning algorithms. You'll 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