Job Summary

We are seeking an experienced NLP Data Scientist to join our AI team and build intelligent Natural Language Processing (NLP) solutions that power enterprise applications. The ideal candidate will develop, fine-tune, and deploy advanced NLP and Large Language Model (LLM) solutions for chatbots, document intelligence, semantic search, sentiment analysis, question answering, and text classification. You will collaborate with Data Scientists, Machine Learning Engineers, Product Managers, and Software Engineers to deliver scalable AI solutions that improve customer experiences and business outcomes.

Key Responsibilities

• Design, develop, and deploy advanced NLP and LLM-based applications.
• Build and optimize models for text classification, named entity recognition (NER), summarization, sentiment analysis, and topic modeling.
• Develop semantic search and Retrieval-Augmented Generation (RAG) solutions using vector databases.
• Fine-tune transformer-based models such as BERT, RoBERTa, T5, Llama, and other open-source LLMs.
• Create conversational AI systems, virtual assistants, and enterprise chatbots.
• Perform text preprocessing, tokenization, feature engineering, and data cleaning.
• Evaluate model performance using appropriate NLP metrics and improve accuracy through experimentation.
• Collaborate with Data Engineers to build scalable data pipelines for text processing.
• Deploy NLP models using cloud platforms and MLOps best practices.
• Monitor production models, identify performance issues, and continuously improve model quality.
• Stay current with the latest advancements in NLP, Generative AI, and transformer architectures.
• Document technical designs, model architectures, and development processes.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Computational Linguistics, or a related field.
• 3–6+ years of experience in Natural Language Processing or Machine Learning.
• Strong programming skills in Python.
• Experience building production-ready NLP applications.
• Hands-on experience with transformer architectures and Large Language Models.
• Strong understanding of statistics, machine learning, and deep learning concepts.
• Experience working with large structured and unstructured datasets.
• Excellent analytical, communication, and problem-solving skills.

Required Technical Skills

Programming

• Python
• SQL

NLP Frameworks

• Hugging Face Transformers
• spaCy
• NLTK
• Gensim
• Sentence Transformers

Machine Learning & Deep Learning

• Scikit-learn
• TensorFlow
• PyTorch

Large Language Models

• Llama
• Mistral
• Gemma
• BERT
• RoBERTa
• T5
• GPT-based APIs

Generative AI

• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• AI Agents
• Function Calling

Vector Databases

• Pinecone
• Weaviate
• Chroma
• FAISS
• Milvus

Cloud Platforms

• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)

MLOps & Deployment

• Docker
• Kubernetes
• MLflow
• Git
• GitHub Actions
• CI/CD Pipelines

Data Visualization

• Power BI
• Tableau
• Matplotlib
• Plotly

Preferred Qualifications

• Experience with enterprise chatbot development.
• Knowledge of document AI and OCR pipelines.
• Experience implementing semantic search and knowledge retrieval systems.
• Familiarity with LangChain, LlamaIndex, or similar AI orchestration frameworks.
• Experience working in Agile/Scrum development environments.
• Contributions to open-source NLP or AI projects are a plus.

Preferred Certifications

• Microsoft Certified: Azure AI Engineer Associate
• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• TensorFlow Developer Certificate
• Databricks Certified Machine Learning Professional

Benefits

• Competitive salary and annual performance bonus
• Medical, dental, and vision insurance
• Paid time off (PTO) and paid holidays
• Flexible remote or hybrid work options
• Professional development and certification reimbursement
• Employee wellness programs
• Career growth opportunities
• Collaborative and innovative work environment