Data Scientist

Responsibilities

• Design, fine-tune, and deploy Large Language Models (LLMs) such as LLaMA, GPT, and other state-of-the-art models.
• Develop and maintain custom NLP pipelines for tasks like text generation, summarization, sentiment analysis, and more.
• Utilize Hugging Face's ecosystem (Transformers, Datasets, Accelerate) for model training, inference, and optimization.
• Collaborate on building and implementing MLOps pipelines for efficient model deployment and scalability.
• Experiment with domain-specific pretraining and fine-tuning to create models that meet business needs.
• Analyze and preprocess datasets for training and evaluation, ensuring data quality and compliance.
• Collaborate with cross-functional teams to integrate AI solutions into products and services.
• Stay updated with advancements in AI/ML research and contribute to open-source projects or internal knowledge bases.

Skills and Qualifications

Required

• Bachelor's or Masters degree in Computer Science, Data Science, AI/ML, or a related field.
• Proficiency in Python and experience with libraries such as PyTorch and TensorFlow.
• Hands-on experience with Hugging Face Transformers and datasets.
• Strong understanding of LLM architectures, including attention mechanisms and transformer models.
• Experience in fine-tuning and deploying LLMs like LLaMA, GPT, BERT, or similar.
• Familiarity with distributed training frameworks (e.g., PyTorch Lightning, Accelerate).
• Proficiency in using cloud platforms such as AWS, Azure, or Google Cloud for model training and deployment.
• Strong problem-solving skills and an ability to work on ambiguous and complex challenges.