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    Home/Jobs/Gen AI Developer

    Gen AI Developer

    SpritleOneAI

    Chennai
    2+ years
    Today
    ₹8–19 LPA
    Full-time
    Onsite

    Skills Required

    LLM
    RAG
    LangChain
    vLLM
    Hugging Face Transformers
    LangGraph
    CrewAI
    MCP
    Pinecone
    Weaviate
    Qdrant
    Chroma
    Ollama
    LoRA
    QLoRA

    Description

    We are looking for a Gen AI Developer to implement and optimize Retrieval-Augmented Generation (RAG) pipelines and collaborate with cross-functional teams to integrate AI solutions into applications.

    Company: SpritleOneAI

    Role: Gen AI Developer

    Experience:

    • 2+ years of experience as a Gen AI developer

    Key Skills:

    • LLM Frameworks & Orchestration (LangChain/LangGraph/CrewAI, MCP, RAG)
    • Vector Databases (Pinecone/Weaviate/Qdrant/Chroma)
    • Model Deployment & Fine-tuning (vLLM, Ollama, LoRA/QLoRA)
    • Programming & Databases (Python, Java, SQL)
    • ML/DL Frameworks (PyTorch, TensorFlow, Hugging Face Transformers)

    Role Focus:

    • Implement and optimize Retrieval-Augmented Generation (RAG) pipelines
    • Apply LoRA (Low-Rank Adaptation) and QLoRA (Quantized LoRA) techniques
    • Collaborate with software engineers and Ops teams to deploy ML/AI models
    • Contribute to building and maintaining end-to-end ML pipelines
    • Collaborate with cross-functional teams to integrate AI solutions into applications

    Nice to have:

    • A keen interest in learning new technologies and staying updated with the latest trends

    Other:

    • Stay updated with the latest advancements in AI, ML, and Deep Learning

    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.

    Large Language Models: Application through Production

    edX

    Production-focused LLM course covering deployment, monitoring, and scaling.

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