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Lead Data Scientist -- NLP, Deep Learning, GenAI (10 Years)

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Job Description - Lead Data Scientist -- NLP, Deep Learning, GenAI (10 Years)

Description

Key Responsibilities

  • Develop end‑to‑end NLP and GenAI solutions, including text classification, summarization, RAG systems, conversational AI, and document intelligence pipelines.
  • Build, fine‑tune, and evaluate LLM-based models using transformer architectures (BERT, GPT, T5, LLaMA, etc.).
  • Design and implement custom NLP workflows, embeddings, semantic search, vector databases, and prompt engineering strategies.
  • Develop scalable advanced ML models leveraging deep learning, traditional ML, and hybrid architectures.
  • Deploy models and AI apps using modern MLOps practices across cloud environments (Azure preferred).
  • Collaborate closely with product, engineering, and business teams to translate requirements into AI-driven solutions.
  • Monitor model performance, conduct error analysis, and continuously optimize pipelines.

 

Required Skills

  • 10+ years of experience in data science with deep hands‑on expertise in NLP and Generative AI.
  • Proficient in transformer models, embeddings, and modern NLP libraries (Hugging Face, spaCy, NLTK).
  • Strong Python skills with experience in PyTorch/TensorFlow for advanced model development.
  • Practical experience building RAG architectures, vector search, and prompt optimization.
  • Solid understanding of MLOps, model deployment, monitoring, and productionization.
  • Strong problem‑solving abilities with excellent communication and stakeholder engagement skills.
Original job Lead Data Scientist -- NLP, Deep Learning, GenAI (10 Years) posted on GrabJobs ©. To flag any issues with this job please use the Report Job button on GrabJobs.
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About the Company

Enable Dataorporated

Enable Data is a leading provider of advanced application, data and cloud engineering services. We have developed deep expertise across a number of industries and our consultants work with customers to leverage modern solutions to drive increased value across their business ecosystem.

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