01Overview
5+ years of experience in AI/ML engineering with strong software development fundamentals.Strong programming skills in Python; knowledge of SQL and Java is an advantage.Hands-on experience in Machine Learning, Deep Learning, and Natural Language Processing (NLP).Experience building Generative AI applications using Large Language Models (LLMs).Strong expertise in Prompt Engineering, Retrieval-Augmented Generation (RAG), AI Agents, and Agentic AI.Hands-on experience with AI frameworks such as LangChain, LangGraph, LlamaIndex, Hugging Face, and OpenAI SDK.Experience working with vector databases such as Pinecone, FAISS, ChromaDB, Milvus, or Weaviate.Proficiency in ML frameworks and libraries including PyTorch, TensorFlow, Scikit-learn, XGBoost, Pandas, and NumPy.Experience developing and deploying REST APIs using FastAPI or Flask.Good understanding of MLOps, including MLflow, Kubeflow, model deployment, monitoring, model versioning, and CI/CD pipelines.Experience with Docker, Kubernetes, Git, GitHub Actions, or Jenkins.Hands-on experience with at least one cloud platform: AWS, Azure, or GCP, including AI services such as SageMaker, Azure OpenAI, AWS Bedrock, or Vertex AI.Experience working with relational and NoSQL databases such as PostgreSQL, MySQL, MongoDB, or Redis.Knowledge of software engineering best practices, scalable system design, and Agile development methodologies.Excellent analytical, problem-solving, communication, and stakeholder management skills.Ability to work collaboratively in cross-functional teams and deliver production-grade AI solutions. .
