Generative AI Engineer - Machine Learning

GenAI / AI-ML EngineerLocation : Gurugram (Hybrid)Employment Type : Full-TimeExperience : 4 to 6 YearsPreference : Noida/NCR Local Candidates OnlyKey Responsibilities :- Design, develop, and deploy scalable AI/ML and Generative AI solutions.- Build and optimize RAG (Retrieval-Augmented Generation) pipelines using modern frameworks and vector databases.- Develop LLM-powered applications leveraging prompt engineering, AI agents, and multi-agent workflows.- Fine-tune, evaluate, and monitor machine learning and deep learning models.- Build REST APIs and backend services for AI applications.- Design data preprocessing, feature engineering, and model evaluation pipelines.- Integrate structured and unstructured data sources to deliver contextual AI solutions.- Collaborate with cross-functional teams including Data Engineering, DevOps, and Product teams.- Ensure scalability, reliability, and performance of AI applications in production environments.Programming & Development :- Strong hands-on experience in Python and SQL.- Experience building APIs using FastAPI or similar frameworks.- Strong understanding of software engineering best practices and Agile methodologies.Machine Learning & Deep Learning :- Hands-on experience with: Scikit-learn, TensorFlow, PyTorch, Keras.- Strong understanding of: Regression, Classification, Clustering, Feature Engineering, Model Evaluation, Hyperparameter Tuning.NLP & Generative AI :- Minimum 1+ year of hands-on experience in GenAI/LLM projects.- Experience with: Large Language Models (LLMs), Prompt Engineering, RAG Architectures, Agentic AI / Multi-Agent Systems, LangChain, LangGraph, OpenAI APIs, Hugging Face, LangSmith.RAG & Vector Databases :- Experience working with: Pinecone, FAISS.- Knowledge of embedding models and semantic search architectures.- Experience with RAG evaluation metrics such as RAGAS, BLEU, and ROUGE.Cloud & DevOps :- Hands-on experience with AWS services: EC2, S3, SageMaker, Bedrock.- Experience with Docker, Git, JIRA, and CI/CD practices. (ref:hirist.tech)