Job Title : Data Scientist - NLP & Generative AI

Experience : 5+ Years

Location : Chennai / Coimbatore / Bangalore / Pune

Job Type : Full-Time / Permanent

Work Mode : Hybrid / Onsite (based on client/project need)

Key Responsibilities :

- Design and develop NLP and Generative AI-based solutions to extract, interpret, and generate meaningful information from unstructured data.

- Build and deploy machine learning and deep learning models using frameworks like TensorFlow, PyTorch, or Hugging Face.

- Work with large-scale datasets to build predictive and prescriptive models, ensuring model interpretability and accuracy.

- Develop and expose AI capabilities through RESTful APIs using FastAPI with strong Object-Oriented Programming (OOP) practices.

- Apply OpenCV and computer vision techniques for tasks like image classification, detection, and transformation when applicable.

- Use Azure ML Services and related Azure stack components (Blob Storage, Azure Functions, Logic Apps) for model training, versioning, deployment, and monitoring.

- Collaborate with cross-functional teams including Data Engineers, MLOps Engineers, and Product Owners to deliver end-to-end AI solutions.

- Research and experiment with emerging AI and ML techniques, especially in the field of Generative AI (LLMs, diffusion models, etc.).

Mandatory Skills :

- Python : Strong programming skills with experience in FastAPI, OOPs concepts.

- NLP : Experience in techniques like NER, sentiment analysis, summarization, and transformers.

- Generative AI : Experience in building and fine-tuning models such as GPT, BERT, T5, or other LLMs.

- Machine Learning & Deep Learning : Practical exposure to supervised, unsupervised, and reinforcement learning.

- Computer Vision : Hands-on with OpenCV and deep learning-based vision models.

- Azure AI/ML Ecosystem : Deployment and management of models using Azure ML services.

Preferred Skills :

- Knowledge of vector databases like FAISS, Weaviate, or Pinecone.

- Experience with prompt engineering and Retrieval-Augmented Generation (RAG).

- Familiarity with MLOps practices.

- Understanding of data labeling, model versioning, CI/CD pipelines for ML.

- Experience with Docker/Kubernetes for model packaging and deployment.

Qualifications :

- Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or related fields.

- Proven track record of delivering AI solutions in a production environment.

- Excellent problem-solving, analytical thinking, and communication skills.