AI/ML Developer (LLMs, NLP, and AI Applications)
Summary
Build and deploy LLM/NLP models using Hugging Face, LangChain, and cloud AI services; implement RAG pipelines and vector search for AI-driven chatbots and Q&A systems.
- Develop and fine-tune LLMs and NLP models using Hugging Face Transformers, OpenAI APIs, and LangChain
- Implement retrieval-augmented generation (RAG) for intelligent AI-driven question answering and chatbot applications
- Build and deploy AI models using FastAPI, Flask, and cloud-based inference engines (Azure ML, AWS SageMaker, GCP AI Platform)
- Optimize embedding search and vector retrieval using FAISS, Pinecone, and ANN-based search algorithms
- Work on AI model deployment, API integration, and real-time AI application development in production environments
Requirements
- Bachelor's or Master's degree in Artificial Intelligence, Computer Science, Data Science, or a related field
- Atleast 2-4 years of experience in AI/ML development, NLP, or LLM-based application engineering
- Proficiency in Python, with experience in AI/ML frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers
- Strong experience with OpenAI APIs, LangChain, and fine-tuning LLMs for domain-specific applications
- Expertise in developing and deploying AI-powered applications using FastAPI, Flask, or Django
- Hands-on experience with cloud-based AI services such as Azure ML, AWS SageMaker, or GCP AI Platform
- Knowledge of retrieval-augmented generation (RAG) and its implementation for AI-driven automation
- Proficiency in working with vector databases like FAISS, Pinecone, and ChromaDB for efficient search and retrieval
- Familiarity with containerization and orchestration tools such as Docker and Kubernetes for scalable AI deployment
- Strong problem-solving skills with the ability to troubleshoot and optimize AI models for realworld performance
- Excellent communication and teamwork skills to collaborate with AI researchers, engineers, and business teams