Senior Data Scientist

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 Google Cloud Platform 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 Google Cloud Platform services to deploy, monitor, and scale AI/ML workloads in production environments.