Description

In this role, you will:

  • Conduct deep research on the foundations and capabilities of LLMs.
  • Design and implement innovative research projects to explore the application of LLMs for code understanding and generation.
  • Develop and evaluate novel techniques for LLM fine-tuning and adaptation to the specific needs of legacy codebases.
  • Collaborate with engineers and other scientists to integrate LLM solutions seamlessly into the Legacy Leap platform.
  • Stay up-to-date on the latest advancements in LLM research and present findings at conferences and within the company.
  • Build a RAG-based solution and leverage Vector DB, Graph DB, chunking, ranking, indexing, semantic search, etc.

You are the ideal candidate if you have:

  • Strong foundation skills in AI/ML systems
  • Hands-on experience of working with LLMs
  • Proven experience conducting deep research on LLMs, with a strong understanding of their architecture, training methods, and capabilities.
  • Expertise in natural language processing (NLP) techniques, including text representation, machine translation, and text summarization.
  • A solid foundation in machine learning fundamentals, including deep learning architectures and optimization algorithms.
  • Excellent programming skills in Python, with experience using popular deep learning libraries (e.g., TensorFlow, PyTorch).
  • Excellent communication and collaboration skills, with the ability to effectively present complex technical concepts to technical and non-technical audiences.
  • A passion for innovation and a desire to push the boundaries of what's possible with LLMs.
  • Knowledge of LLM evaluation methodologies

 

Bonus points for:

  • Experience working with LLM for codebase
  • Experience in building and deploying real-world LLM applications.
  • Proficiency in cloud computing platforms (e.g., AWS, Azure, GCP).
  • A strong publication record in top AI and NLP conferences and journals.

Key Skills
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