LLM Model Developer

Project Role : LLM Model Developer Project Role Description : Fine-tunes Large Language Models with emphasis on instruction fine-tuning and domain adaptation to enhance model relevance and performance in specific contexts. Must have skills : Large Language Models (LLMs) Good to have skills : NA Minimum 5 year(s) of experience is required Educational Qualification : 15 years full time education

Summary:

As an LLM Model Developer, a typical day involves refining and adapting large language models to better suit specific domains and instructions. This role requires continuous engagement with model tuning processes to improve the relevance and effectiveness of the models in various contexts. The workday includes analyzing model outputs, iterating on fine-tuning strategies, and ensuring that the models perform optimally for targeted applications. Collaboration with different teams to align model capabilities with project goals is a key aspect, alongside monitoring advancements in the field to incorporate innovative approaches into the development cycle.

Roles & Responsibilities:

• Expected to be an SME, collaborate and manage the team to perform.
• Responsible for team decisions.
• Engage with multiple teams and contribute on key decisions.
• Provide solutions to problems for their immediate team and across multiple teams.
• Lead the development and implementation of fine-tuning strategies to enhance model accuracy and domain specificity.
• Facilitate knowledge sharing and skill development within the team to foster continuous improvement.
• Coordinate cross-functional efforts to integrate model outputs into broader project frameworks.
• Support junior team members by providing guidance and technical assistance to help them grow professionally.

Professional & Technical Skills:

• Must To Have Skills: Proficiency in Large Language Models (LLMs).
• Experience in fine-tuning techniques and domain adaptation for language models.
• Strong understanding of natural language processing concepts and methodologies.
• Ability to analyze and interpret model performance metrics to drive improvements.
• Familiarity with programming languages commonly used in model development such as Python.