Key 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 settings.
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.
Pay: Up to ₹2,000,000.00 per year
Work Location: In person
📌 Genai / Ai Ml Engineer Gurugram
🏢 IAT Networks
📍 Gurugram
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