Data Scientist - NLP/Generative AI in Bombay, भारत

Location : Mumbai / Bangalore (Mumbai Preferred)Experience : 2 - 3 YearsKey Responsibilities : - Develop and deploy Machine Learning, NLP, and Generative AI solutions for business use cases.- Design and implement text analytics models to derive insights from large volumes of structured and unstructured data.- Build and optimize NLP pipelines for classification, information extraction, semantic search, and insight generation.- Develop Document Intelligence solutions leveraging OCR, Vision AI, and Large Language Models.- Create end-to-end AI solutions, including model development, deployment, monitoring, and post-production support.- Collaborate with business stakeholders to understand requirements and translate them into scalable AI products.- Evaluate and implement emerging AI and GenAI technologies to solve business https://jobeax.com/link/23t36DA6vfeJsEFu Skills & Experience : Machine Learning & Data Science : - Strong foundation in Machine Learning, Statistics, and Applied Data Science.- Experience delivering ML solutions in production environments.- Experience handling large-scale datasets (200K+ records).NLP & Text Analytics : Hands-on experience in : - Text Classification- Named Entity Recognition (NER)- Information Extraction- Semantic Search- Topic Modeling- Text Summarization- Insight Generation from Unstructured TextExperience with : - BERT- Sentence Transformers- Transformer Architectures- Embeddings and Vector RepresentationsGenerative AI : - Experience working with Large Language Models (LLMs).- Understanding of Prompt Engineering and GenAI application development.- Experience implementing business-focused GenAI use https://jobeax.com/link/4sh1Kz1YEQpdQVpm AI & Document Intelligence : Experience with : - OCR Technologies- Amazon Textract or equivalent tools- Vision Language Models (VLMs)- PDF and Document Information Extraction- Intelligent Document Processing SolutionsDevelopment & Deployment : - Strong programming skills in Python.- Experience deploying AI models into production.- Exposure to APIs, cloud platforms, and MLOps practices.- Experience supporting and maintaining deployed AI solutions. (ref:hirist.tech)