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Senior NLP Research Engineer

Senior NLP Research Engineer

YO HR ConsultancyNoida
19 days ago
Job description

Senior NLP Research Engineer

Location - Noida

Experience - 4 to 6 years

Must have :

  • Experience in NLP, Machine Learning, or Deep Learning.
  • Experience in working with VLMs and LLMs.
  • Experience with tools such as Hugging Face, LangChain,LLama.cpp, TensorFlow / PyTorch.
  • Hands-on experience with vector databases (e.g., FAISS, Pinecone, Weaviate) and RAG frameworks
  • Strong programming skills in Python and some experience with ML Ops or cloud platforms (AWS / GCP / Azure).
  • Deep understanding of NLP techniques including basics such as NER, text classification, embeddings, tokenization, Transformers , loss functions etc.

Roles and Responsibilities :

Looking for a talented and driven Senior NLP Research Engineer to join our AI / ML team. In this role, youll design and implement advanced natural language processing models that interpret metadata and user queries across complex video datasets. Youll also contribute to the development of Generative AI-based assistants, integrated into our video management ecosystem, enhancing user experience through natural interaction and smart search.

  • Design, develop, Train, fine-tune, and deploy LLM-based NLP models for various enterprise use cases.
  • Experience in Designing the network from scratch according to the problem statement given.
  • Experience in training methodologies to handle the large dataset to train the networks.
  • Collaborate with product, engineering, and data teams to integrate NLP solutions into production-grade systems.
  • Build and optimize custom pipelines for document intelligence, question answering, summarization, and conversational AI.
  • Experience and understanding with state-of-the-art open-source LLMs (e.g.,GPT, LLaMA, Claude, Falcon etc.).
  • Implement prompt engineering, retrieval-augmented generation (RAG), and fine-tuning strategies.
  • Ensure ethical, safe, and scalable deployment of LLM-based systems..
  • Ensure model reliability safeDesign, develop, Train, fine-tune, and deploy LLM-based NLP models for various enterprise use cases.ty, performance, and compliance using evaluation and monitoring frameworks.
  • Stay updated with the latest research in GenAI and NLP, and apply relevant findings to improve current systems.

    • (ref : hirist.tech)

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