Description

Experience: 12+ Years in AI/ML

MUST-HAVE SKILLS
12+ years of AI/ML experience
Strong proficiency in Python
Strong NLP expertise
Text Classification & Clustering
Strong SQL & Data Analysis experience
Hands-on experience with LLMs
Prompt Engineering
LLM Evaluation Frameworks
Retrieval-Augmented Generation (RAG)
Experience designing scalable AI/ML solutions for high-volume applications

LLM / NLP TECHNOLOGIES
Python / Machine Learning:
Python | NumPy | Pandas | Scikit-learn | XGBoost
NLP:
spaCy | Hugging Face Transformers | NLTK | Sentence-Transformers
LLM Frameworks:
LangChain | LlamaIndex | OpenAI SDK
Vector Databases:
FAISS | Pinecone | Weaviate | Qdrant

GOOD TO HAVE
Agentic AI & Multi-Agent Orchestration
LangGraph | AutoGen | CrewAI
LLMOps / MLOps experience in production environments
MLflow | Weights & Biases | BentoML | Airflow
Cloud experience

DATA & SQL
Strong experience with data analysis and querying using:
SQL | Oracle | MySQL | SQLAlchemy

ROLE OVERVIEW
Design and architect scalable AI/ML and LLM solutions for high-volume customer interactions.
Develop advanced NLP solutions including text classification, clustering, semantic understanding, and language processing.
Build and optimize LLM-powered applications using prompt engineering, evaluation frameworks, and RAG architectures.
Develop production-ready AI solutions using Python and modern ML/NLP frameworks.
Work with vector databases and embedding technologies to develop efficient semantic search and RAG pipelines.
Establish AI/ML architecture, engineering best practices, and scalable development standards.
Collaborate with cross-functional teams to drive AI innovation and production deployment.
Support model evaluation, monitoring, optimization, and continuous improvement.
Contribute to Agentic AI and multi-agent systems where applicable.
Implement LLMOps/MLOps practices to ensure AI solutions are reliable, scalable, observable, and production-ready

Key Skills

Education

Any Graduate