Home/Jobs/AI/ML Engineer AI/ML Engineer Shreem Talent Bridge Gurugram 4-6 years Today $18.1K–24.1K/yr Full-time Hybrid Skills Required LLM RAG Agentic AI Gen AI LangChain OpenAI Hugging Face RAGAS Prompt Engineering LangGraph Pinecone FAISS Embedding Models Semantic Search BLEU Description GenAI / AI-ML Engineer role focused on building and deploying scalable AI, ML, and Generative AI solutions. The position is based in Gurugram in a hybrid setup.

Role: GenAI / AI-ML Engineer Location: Gurugram (Hybrid) | Hybrid remote in Gurgaon, Haryana Experience 4–6 years

1+ year of hands-on experience in GenAI/LLM projects Responsibilities Design, develop, and deploy scalable AI/ML and Generative AI solutions

Build and optimize RAG pipelines using modern frameworks and vector databases

Develop LLM-powered applications using 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 for contextual AI solutions

Collaborate with Data Engineering, DevOps, and Product teams

Ensure scalability, reliability, and performance of AI applications in production environments More Skills Python, SQL, FastAPI, Scikit-learn, TensorFlow, PyTorch, Keras, Large Language Models (LLMs), Multi-Agent Systems, OpenAI APIs, LangSmith,



semantic search architectures, RAG evaluation metrics, ROUGE, AWS, EC2, S3, SageMaker, Bedrock, Docker, Git, JIRA, CI/CD, REST APIs, backend services, data preprocessing, feature engineering, model evaluation, software engineering best practices, Agile methodologies Other Employment type: Full time

Budget: 15 LPA to 20 LPA, flexible

Preference: Noida/NCR local candidates only

Pay: ₹1,500,000.00 to ₹2,000,000.00 per year Follow for Daily AI Tutorials Prepare for this role Recommended resources to build the skills for this position. Sponsored. Generative AI with Large Language Models Coursera Comprehensive LLM course covering transformer architecture, fine-tuning, RLHF, and deployment. Functions, Tools and Agents with LangChain Coursera Advanced LangChain covering function calling, tool use, and conversational agents.

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