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GenAI / AI-ML Engineer

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Onsite

GenAI / AI-ML Engineer

TaskNera

GenAI / AI-ML Engineer

Skills

SQL QueriesData EngineeringDeep LearningDockerPythonKerasPyTorchTensorFlowAmazon EC2Machine LearningAIAWSFastAPI

2 months ago

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Important information


Contract type:

Permanent

Work mode:

Onsite

Published on:

24 August 2026

What they need


About the Role
We are seeking an experienced GenAI / AI-ML Engineer to design, develop, and deploy scalable Generative AI and Machine Learning solutions. In this role, you will build modern RAG pipelines, deploy multi-agent workflows, fine-tune models, and integrate scalable backend APIs for enterprise-grade applications.
Note: This position is open exclusively to local candidates in Noida/NCR who are immediate joiners or currently serving their notice period.
Key Responsibilities
GenAI & Agentic Systems: Develop LLM-powered applications utilizing prompt engineering, AI agents, and multi-agent workflows (LangChain, LangGraph).
RAG Pipelines: Build, optimize, and evaluate Retrieval-Augmented Generation (RAG) pipelines using modern vector databases and frameworks like RAGAS.
Backend Integration: Write robust Python code and build high-performance REST APIs using FastAPI to support AI models in production.
ML/DL Engineering: Design end-to-end data preprocessing, feature engineering, fine-tuning, and model evaluation pipelines using Scikit-learn, PyTorch, TensorFlow, and Keras.
Cloud & DevOps: Containerize applications using Docker and deploy scalable models on AWS (SageMaker, Bedrock, EC2, S3) with CI/CD integration.
Collaboration: Partner with Data Engineering, DevOps, and Product teams to ensure reliability, security, and performance of production environments.
Requirements
Experience: 4–6 years in core Machine Learning / Deep Learning, with at least 1+ years of dedicated hands-on experience in GenAI/LLM projects.
Programming & Backend: Strong proficiency in Python, SQL, and framework expertise with FastAPI.
GenAI Stack: Hands-on experience with OpenAI APIs, Hugging Face, LangChain, LangGraph, LangSmith, and vector databases (Pinecone, FAISS).
Evaluation Metrics: Practical experience with evaluation frameworks (RAGAS, BLEU, ROUGE) and semantic search architectures.
Cloud Infrastructure: Solid background with AWS services (EC2, S3, SageMaker, Bedrock), Docker, and Git.
Availability: Immediate joiners or candidates currently serving their notice period based in Noida/NCR.

Pay: ₹1,800,000.00 - ₹2,000,000.00 per year

Application Question(s):

  • Are you based in Noida/NCR and available as an immediate joiner (or currently serving your notice period)?
  • Do you have at least 1 year of hands-on experience building GenAI applications using LangChain, LangGraph, or multi-agent workflows?
  • Which vector databases and RAG evaluation tools have you used in production (e.g., Pinecone, FAISS, RAGAS)?
  • How many years of experience do you have building production REST APIs using FastAPI in Python?

Work Location: In person

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