GlobalLogic is seeking an LLM Tuning Engineer to research, design, and implement NLP algorithms with a focus on fine-tuning large language models like BERT and GPT. The role involves developing custom fine-tuning strategies, collaborating with cross-functional teams, and analyzing experimental results to improve model performance. Candidates should have a strong background in NLP, deep learning, and proficiency in Python, TensorFlow, and PyTorch.
Responsibilities
Research, design, and implement pioneering NLP algorithms with a focus on fine-tuning LLMs, including BERT, GPT, and their variants
Develop custom fine-tuning strategies and techniques to optimize performance on specific language tasks and domains
Collaborate with cross-functional teams to integrate fine-tuned LLM solutions into products and services
Stay up-to-date with the latest advancements in NLP, LLMs, and AI technologies, particularly in fine-tuning methodologies
Analyze and interpret experimental results to guide decision-making and improve model performance
Apply creative problem solving and inter-departmental networking to address data and information needs across the enterprise
Share proven techniques with peers through coaching and mentoring
Drive innovation by exploring new experimentation methods and statistical techniques
Requirements
Strong background in NLP, deep learning, and machine learning, with proven track record in fine-tuning LLMs