Texas Instruments (TI) is seeking a PhD student to research and develop cutting-edge Large Language Models (LLMs) and Agentic LLMs for Edge AI applications, focusing on areas like coding generation and optimization, to advance the state-of-the-art in AI and integrate LLMs with other AI techniques for human-like decision-making.
Requirements
- 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
Responsibilities
- 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
- 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
- Do system modeling and simulations for solutions feasibility study
- Define and build system prototypes to demonstrate the functionality and understand application needs and limitations
Other
- Currently enrolled in a PhD program in Computer Science, Electrical and Computer Engineering, or related fields
- Cumulative 3.0/4.0 GPA or higher
- Excellent communication and interpersonal skills, with the ability to work in a dynamic and distributed team
- ECL/GTC Required: Yes
