Senior Generative AI Model Developer

3 days ago

Chennai, Tamil Nadu, India beBeeGenerative Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
AI/ML Engineer Generative AI Specialist

We are seeking a highly motivated AI/ML engineer with extensive experience to lead our team in building and optimizing solutions using Generative AI.

Key Responsibilities:

  • Design, build ML models with a focus on LLMs and Generative AI.
  • Conduct research that contributes to the state-of-the-art in LLM architectures.
  • Expertise in full and parameter-efficient fine-tuning (LoRA, QLoRA, Adapter, Prefix Tuning), instruction tuning, RLHF, and multi-task learning.
  • Proficient in model compression (AWQ, GPTQ, GPTQ-for-LLaMA) and optimized inference engines (vLLM, DeepSpeed, FP6-LLM).
  • Develop and maintain scalable APIs to serve model outputs in production environments.
  • Collaborate with cross-functional teams (product, data and engineering) to identify AI opportunities and deliver solutions.
  • Implement Retrieval-Augmented Generation (RAG) pipelines and integrate vector databases (e.g., FAISS, Pinecone).
  • Database Knowledge : Experience with PostgreSQL.
  • Research and apply the latest techniques in prompt engineering, model compression, and optimization.
  • Monitor, evaluate, and continuously improve model performance

Requirements :

  • Bachelor's or Masters degree in Computer Science, Data Science, AI, or a related field.
  • 7-9 years of hands-on experience in AI/ML development and Expertise in Agentic approach.
  • Strong programming skills in Python and experience with ML frameworks such as Proficiency in TensorFlow, PyTorch, Keras.
  • Experience in distributed training, NVIDIA AI platforms, and cloud/on-premise infrastructure.
  • Familiarity with integrating MCP-based architectures into broader system workflows, ensuring semantic consistency and interoperability.
  • Experience with performance tuning, caching strategies, and cost optimization, particularly in the context of production-grade LLM deployments.
  • Experience with LLMs, including fine-tuning, prompt engineering, and using frameworks like Hugging Face Transformers.
  • Familiarity with GenAI techniques and tools such as LangChain, LangGraph, LLMOps, LoRA, and PEFT.
  • Experience deploying models using FastAPI, Flask, Docker, or on cloud platforms (AWS/GCP/Azure).
  • Understanding of NLP concepts, deep learning architectures, and transformer models

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