Description

>> Design, build, fine-tune, and deploy LLM-based applications using Python

>> Implement and optimize deep learning models for NLP use cases, including text classification, sentiment analysis, and text summarization

>> Develop solutions using prompt engineering techniques

>> Utilize vector databases to store and retrieve model embeddings and AI-generated data

>> Work with deep learning frameworks and libraries such as TensorFlow, PyTorch, and Hugging Face Transformers

>> Apply knowledge of deep learning architectures and techniques

>> Use orchestration frameworks such as LangChain or similar tools

>> Build AI-powered applications using Streamlit, FastAPI, and Flask

>> Deploy and scale machine learning models on Azure and Google Cloud Platform (GCP)

>> Write efficient, well-documented, and maintainable Python code

>> Support CI/CD pipelines for ML and GenAI deployments

>> Apply knowledge of agentic architectures and multi-agent patterns such as AutoGen or similar frameworks

>> Collaborate with cross-functional teams to design scalable AI systems Requirements: >> 6-8 years of overall experience in software development, data analytics, or data science

>> 2+ years of hands-on experience with deep learning, NLP, and Generative AI

>> Strong proficiency in Python >> Experience in deep learning, Natural Language Processing (NLP), and Generative AI

>> Understanding of large language models and their real-world applications

>> Experience managing AI model lifecycle from development to production

>> Experience deploying AI solutions on Azure or GCP

>> Knowledge of healthcare domain workflows and data

>> Familiarity with agentic and multi-agent AI design patterns

Key Skills

Education

Bachelor's degree