Senior Data Scientist (GenAI, LLM & Machine Learning)

Hi , Our client is looking for an Senior Data Scientist (GenAI, LLM & Machine Learning) for a project and below is the detailed requirement. Job Title: Senior Data Scientist (GenAI, LLM & Machine Learning) Location: Raleigh, NC Qualifications & Experience: • Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, or a related field with 6–8+ years of experience in Data Science, Machine Learning, and AI solution development with overall 12-14+ years of experience. • 6+ years of hands-on experience designing, developing, and deploying machine learning models and advanced analytics solutions in enterprise environments. • Strong experience with Large Language Models (LLMs), Generative AI, Prompt Engineering, Retrieval-Augmented Generation (RAG), and model evaluation frameworks. • Advanced proficiency in Python with experience developing scalable AI/ML applications and data processing pipelines. • Hands-on experience with deep learning frameworks including PyTorch, TensorFlow, Keras, and Hugging Face Transformers. • Strong expertise in Natural Language Processing (NLP) techniques and tools such as spaCy, BERT, Word2Vec, Transformers, Flair, and text classification models. • Experience building and maintaining training, validation, benchmarking, and evaluation datasets for AI/ML initiatives. • Knowledge of vector databases and search technologies including ChromaDB, Elasticsearch, OpenSearch, or similar platforms. • Experience working with relational and NoSQL databases such as PostgreSQL, MongoDB, Cosmos DB, or equivalent. • Experience with cloud platforms including AWS, Azure, or GCP for model development, deployment, and scaling. • Understanding of data modeling principles, embeddings, clustering, dimensionality reduction, sequence classification, and predictive analytics. • Exposure to distributed computing technologies such as Spark, Ray, or Scala is highly preferred. • Experience with API development, containerization (Docker/Kubernetes), and MLOps/AIOps practices is highly preferred. • Strong analytical, problem-solving, communication, and stakeholder collaboration skills. Key Responsibilities: • Design, develop, and deploy enterprise-grade AI/ML and Generative AI solutions leveraging Large Language Models (LLMs), NLP techniques, and advanced machine learning methodologies. • Build and optimize Retrieval-Augmented Generation (RAG) pipelines, prompt engineering frameworks, vector embedding solutions, and knowledge retrieval systems. • Develop AI applications tailored for legal document intelligence, document processing, search, summarization, and classification use cases. • Design and implement data pipelines for ingestion, preprocessing, annotation, enrichment, and management of structured and unstructured datasets. • Collaborate closely with legal domain experts, business stakeholders, and engineering teams to understand requirements and translate them into scalable AI solutions. • Conduct model experimentation, benchmarking, evaluation, and performance optimization to improve accuracy, reliability, and business outcomes. • Develop and maintain machine learning models using PyTorch, TensorFlow, Keras, Hugging Face Transformers, and other modern AI frameworks. • Implement NLP solutions involving entity extraction, semantic search, document classification, embeddings, and language understanding tasks. • Build and optimize integrations with vector databases, search platforms, relational databases, and cloud-native services. • Work with AWS, Azure, or GCP services to deploy, monitor, and scale AI/ML workloads in production environments.