Responsibilities:
Develop and fine-tune large language models for specific applications.
Optimize LLMs for performance, scalability, and deployment efficiency.
Collaborate with researchers and data scientists to implement cutting-edge techniques.
Build pipelines for data collection, preprocessing, and model evaluation.
Monitor and address issues in LLM performance and reliability.
Requirements:
Strong experience with Python and AI frameworks like PyTorch or TensorFlow.
Proficiency in transformer architectures (e.g., GPT, BERT).
Expertise in natural language processing (NLP) and large-scale data handling.
Familiarity with distributed training and cloud-based AI environments.
Master’s or Ph.D. in AI, Computer Science, or related field preferred.