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Systems Engineering Intern (Machine Learning)

Lensa
Dallas, TX Intern
POSTED ON 12/29/2025
AVAILABLE BEFORE 1/27/2026
Lensa is a career site that helps job seekers find great jobs in the US. We are not a staffing firm or agency. Lensa does not hire directly for these jobs, but promotes jobs on LinkedIn on behalf of its direct clients, recruitment ad agencies, and marketing partners. Lensa partners with DirectEmployers to promote this job for Texas Instruments. Clicking "Apply Now" or "Read more" on Lensa redirects you to the job board/employer site. Any information collected there is subject to their terms and privacy notice.

We are seeking a highly motivated PhD student to join our Generative AI team this summer to work on cutting-edge Large Language Model (LLM) research and development for Edge AI applications. As a key member of our team, you will focus on advancing the state-of-the-art in LLMs and Agentic LLMs, with applications in coding generation and optimization. Your work will involve exploring innovative approaches to integrate LLMs with other AI techniques to achieve human-like decision-making capabilities.

In this machine learning research engineer intern role, you'll have the chance to:

  • Research and develop novel LLM architectures and training methods to improve performance and efficiency
  • Explore the application of LLMs in coding generation, optimization, and other areas of interest
  • Collaborate with internal business teams to define and implement AI strategies for our products
  • Develop and maintain large-scale deep learning systems, incorporating LLMs and other AI techniques
  • Participate in the design and implementation of advanced Agentic LLM system

About Us

Texas Instruments Incorporated (TI) is a global semiconductor design and manufacturing company that develops analog and embedded processing ICs. By employing the world's brightest minds, TI innovates that shape the future of technology with commits to building a better future. The future which covers from the responsible manufacturing of our semiconductors, to caring for our employees, to giving back to our communities and developing great minds. Put your talent to work with us - change the world, love your job!

Kilby Labs, TI's central technology organization , is a global organization grouped by a variety of research engineers from multiple technology disciplines to deliver semiconductor technologies and solutions for future large volume products in a fast moving pace. The engineer is expected to do system modeling and simulations for solutions feasibility study, define and build system prototypes to demonstrate the functionality and understand application needs and limitations.

Our Generative AI team is at the forefront of AI research, developing and applying AI algorithms, training models, and optimizing hardware and software for real-world problem-solving. We are passionate about harnessing the power of AI to create intelligent systems that can interact, learn, and adapt in complex environments.

Why TI?

  • Engineer your future. We empower our employees to truly own their career and development. Come collaborate with some of the smartest people in the world to shape the future of electronics.
  • We're different by design. Diverse backgrounds and perspectives are what push innovation forward and what make TI stronger. We value each and every voice, and look forward to hearing yours. Meet the people of TI (https://edbz.fa.us2.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX/pages/4012)
  • Benefits that benefit you. We offer competitive pay and benefits designed to help you and your family live your best life. Your well-being is important to us.

About Texas Instruments

Texas Instruments Incorporated (Nasdaq: TXN) is a global semiconductor company that designs, manufactures and sells analog and embedded processing chips for markets such as industrial, automotive, personal electronics, communications equipment and enterprise systems. At our core, we have a passion to create a better world by making electronics more affordable through semiconductors. This passion is alive today as each generation of innovation builds upon the last to make our technology more reliable, more affordable and lower power, making it possible for semiconductors to go into electronics everywhere. Learn more at TI.com .

Texas Instruments is an equal opportunity employer and supports a diverse, inclusive work environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, creed, disability, genetic information, national origin, gender, gender identity and expression, age, sexual orientation, marital status, veteran status, or any other characteristic protected by federal, state, or local laws.

If you are interested in this position, please apply to this requisition.

Minimum Requirements

  • Currently enrolled in a PhD program in Computer Science, Electrical and Computer Engineering, or related fields
  • Cumulative 3.0/4.0 GPA or higher

Preferred Qualifications

  • Solid background in Natural Language Processing, Large Language Models, and Deep Learning frameworks
  • Proven track record of designing, developing, and deploying machine learning models/LLMs as demonstrated by first-authored publications at leading AI/ML workshops or conferences
  • Proficiency in Python, C/C , and software design, including debugging, performance analysis, and optimization
  • Excellent understanding of LLM architectures and transformer-based models
  • Experience with popular deep learning frameworks (e.g., PyTorch, JAX, ONNX) and LLM-specific libraries (e.g., transformers, trl, vllm)
  • Knowledge of few-shot learning, transfer learning, and fine-tuning
  • Knowledge of LLM performance evaluation
  • Knowledge of reinforcement learning for LLM;
  • Knowledge of LLM post-training implementation, including PPO, DPO, and GRPO
  • Experience with Agentic AI implementation with tool calling
  • Excellent communication and interpersonal skills, with the ability to work in a dynamic and distributed team

ECL/GTC Required: Yes

If you have questions about this posting, please contact support@lensa.com

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