Location : Mumbai / Bangalore (Mumbai Preferred)

Experience : 2 - 3 Years

Key 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 problems.

Required 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 Text

Experience with :

- BERT

- Sentence Transformers

- Transformer Architectures

- Embeddings and Vector Representations

Generative AI :

- Experience working with Large Language Models (LLMs).

- Understanding of Prompt Engineering and GenAI application development.

- Experience implementing business-focused GenAI use cases.

Vision AI & Document Intelligence :

Experience with :

- OCR Technologies

- Amazon Textract or equivalent tools

- Vision Language Models (VLMs)

- PDF and Document Information Extraction

- Intelligent Document Processing Solutions

Development & 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.