Description

Lead research and implementation of Large Language Models for code understanding and generation.

Responsibilities

• Conduct deep research into LLM foundations, architectures, and capabilities.
• Design and implement research projects for LLM applications in code generation and legacy codebase adaptation.
• Develop and evaluate novel fine-tuning and adaptation techniques tailored to specific codebase needs.
• Build RAG-based solutions utilizing Vector DB, Graph DB, chunking, ranking, indexing, and semantic search.
• Collaborate with engineers to integrate LLM solutions into the Legacy Leap platform.

Required Skills

• 6+ years of experience in Data Science and AI/ML systems.
• Hands-on experience working with LLMs and Generative AI.
• Proven expertise in conducting deep research on LLM architectures and training methods.
• Strong proficiency in Python and deep learning libraries such as PyTorch or TensorFlow.
• Deep understanding of NLP techniques, including text representation, machine translation, and summarization.
• Solid foundation in machine learning fundamentals, deep learning architectures, and optimization algorithms.
• Practical knowledge of LLM evaluation methodologies.
• Experience implementing RAG architectures.

Preferred Skills

• Experience applying LLMs specifically to codebase tasks.
• Background in building and deploying real-world LLM applications.
• Proficiency in cloud computing platforms like AWS, Azure, or GCP.

Key Skills

Education

Not specified