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AI/ML Engineer

3 - 8 years

9 - 19 Lacs

Posted:1 day ago| Platform: Naukri logo

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Hybrid

Job Type

Full Time

Job Description

: Generative AI Engineer

: 3 to 5 years

:

We are looking for a Generative AI Engineer with 3 to 5 years of hands-on experience in Retrieval-Augmented Generation (RAG), Agentic AI, and Data Pipelines. The ideal candidate will have real-time experience in developing and deploying AI-powered solutions, working with advanced language models, and optimizing AI workflows for production environments.

:

  • Implement and optimize Retrieval-Augmented Generation (RAG) techniques to enhance AI response quality.
  • Develop and deploy Agentic AI systems capable of autonomous decision-making and task execution.
  • Build and manage data pipelines for processing, transforming, and feeding structured/unstructured data into AI models.
  • Ensure scalability, performance, and security of AI-driven solutions in production environments.
  • Collaborate with cross-functional teams, including data engineers, software developers, and product managers.
  • Conduct experiments and evaluations to improve AI system accuracy and efficiency.
  • Stay updated with the latest advancements in AI/ML research, open-source models, and industry best practices.

& :

  • Hands-on experience with RAG architectures, including vector databases (e.g., Pinecone, ChromaDB, Weaviate, OpenSearch, FAISS).
  • Experience in building AI agents using LangChain, LangGraph, CrewAI, AutoGPT, or similar frameworks.
  • Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow.
  • Knowledge of cloud platforms (AWS/GCP/Azure) and containerization technologies (Docker, Kubernetes).
  • Familiarity with LLM APIs (OpenAI, Anthropic, Mistral, Cohere, Llama, etc.) and their integration in applications.
  • Strong understanding of vector search, embedding models, and hybrid retrieval techniques.
  • Experience with optimizing inference and serving AI models in real-time production systems.

-- :

  • Experience with multi-modal AI (text, image, audio) and LLM fine tuning.
  • Familiarity with privacy-preserving AI techniques and responsible AI frameworks.
  • Understanding of MLOps best practices, including model versioning, monitoring, and deployment automation.

____________________________________________________________________________

"Python/Gen AI Developer"

Experience: 5 to 8

Location: Coimbatore/Remote

Notice Period: Immediate Joiners are Preferred

:

  • Design, develop, and fine-tune Large Language Models (LLMs) for various in-house applications.
  • Implement and optimize Retrieval-Augmented Generation (RAG) techniques to enhance AI response quality.
  • Develop and deploy Agentic AI systems capable of autonomous decision-making and task execution.
  • Build and manage data pipelines for processing, transforming, and feeding structured/unstructured data into AI models.
  • Ensure scalability, performance, and security of AI-driven solutions in production environments.
  • Collaborate with cross-functional teams, including data engineers, software developers, and product managers.
  • Conduct experiments and evaluations to improve AI system accuracy and efficiency.
  • Stay updated with the latest advancements in AI/ML research, open-source models, and industry best practices.

& :

  • Strong experience in LLM fine-tuning using frameworks like Hugging Face, DeepSpeed, or LoRA/PEFT.
  • Hands-on experience with RAG architectures, including vector databases (e.g., Pinecone, ChromaDB, Weaviate, OpenSearch, FAISS).
  • Experience in building AI agents using LangChain, LangGraph, CrewAI, AutoGPT, or similar frameworks.
  • Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow.
  • Experience in Python web frameworks such as FastAPI, Django, or Flask.
  • Experience in designing and managing data pipelines using tools like Apache Airflow, Kafka, or Spark.
  • Knowledge of cloud platforms (AWS/GCP/Azure) and containerization technologies (Docker, Kubernetes).
  • Familiarity with LLM APIs (OpenAI, Anthropic, Mistral, Cohere, Llama, etc.) and their integration in applications.
  • Strong understanding of vector search, embedding models, and hybrid retrieval techniques.
  • Experience with optimizing inference and serving AI models in real-time production systems.

-- :

  • Experience with multi-modal AI (text, image, audio).
  • Familiarity with privacy-preserving AI techniques and responsible AI frameworks.
  • Understanding of MLOps best practices, including model versioning, monitoring, and deployment automation.

    Role & responsibilities

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