Advancing the state-of-the-art in LLM architectures, Agentic LLM, and Reasoning LLM for Edge AI applications, and integrating LLMs with domain knowledge, tools, and other AI techniques to achieve human-like decision-making capabilities for business impact.
Requirements
- Strong background in Natural Language Processing, Large Language Models, and Deep Learning frameworks
- Proven track record of designing, developing, and deploying machine learning models/LLMs that drive business value
- 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)
- Strong foundation in text processing, tokenization, and embedding techniques
- Knowledge of few-shot learning, transfer learning, and fine-tuning
Responsibilities
- Explore the application of LLMs in code generation, evaluation, and optimization
- Conduct research and development on novel and efficient LLM architectures, training algorithms, and post-training algorithms
- Design and develop new reasoning models with domain-specific knowledge
- Design and implement advanced Agentic LLM system for complex task automations
- Collaborate with system teams and internal business teams to define and implement AI/ML solutions for core business
Other
- Currently pursuing a doctoral degree in Electrical Engineering, Computer Engineering, Electrical and Computer Engineering or related field
- Cumulative 3.0/4.0 GPA or higher
- Demonstrated analytical and problem solving skills
- Strong written and verbal communication skills
- Ability to work in teams and collaborate effectively with people in different functions
