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NLP Technical Architect


Information Technology


Noida, India

Reporting to:


Employment type:


We are looking for NLP Technical Architect to design and develop efficient self-learning NLP products.

Skills Required

  • 10+ years’ experience with proven 7+ years’ relevant experience as an NLP Developer and Architect.
  • Work Experience in creating NLP pipelines for processing large amount of document corpus, web crawlers/ scrapers, NLP based chatbots (like Rasa)
  • Experience with machine learning libraries (like spacy, scikit-learn), frameworks (like Keras or PyTorch), statistics and classification algorithms.
  • Understanding of NLP techniques for text representation, semantic extraction techniques, data structures and modelling.
  • Working experience in NLP application areas - Sematic Web and Ontologies, Document Classification, Question-Answer Matching, Text Summarization, Machine Translation, Sentiment Analysis. Have worked with RNN, LSTM etc
  • Working knowledge of relational and NO-SQL database systems.
  • Knowledge of Python, Java and R. Any other experience with programming languages will be appreciated (but must NOT be the primary skill)
  • Working knowledge of deploying and using Machine Learning environments on Cloud (Azure, AWS) and DevOps (CI/ CD) experience
  • Ability to write robust and testable code
  • Strong communication skills
  • An analytical mind with problem-solving abilities


As well as possessing the required technical skills, you will be a confident individual capable of working in a busy development environment with a focus on delivering efficient self-learning NLP products.


  • Effectively understand the problem and then design most efficient NLP software architecture
  • Study and transform data science prototypes
  • Select appropriate annotated datasets for Supervised Learning methods
  • Use effective text representations to transform natural language into useful features
  • Find and implement the right algorithms and tools for NLP tasks
  • Develop NLP systems according to requirements
  • Train the developed model and run evaluation experiments
  • Perform statistical analysis of results and refine models
  • Extend ML libraries and frameworks to apply in NLP tasks
  • Remain updated in the rapidly changing field of machine learning
  • Working closely with IT Operations to ensure high standards of delivery.

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