Resilinc | Jobs | NLP ML Engineer | BigDataKB.com | 17-02-22

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Job Location: Pune

We are a leading Data Platform that uses AI to help Enterprises leverage Supply Chain Data at a global scale . We have one of the largest repositories of supply chain mapping data worldwide . We help Fortune 200 corporations to d igitiz e their Supply Chain by mapping the partners, analyzing the risk, assess capacity and Business Continuity, using AI based data rich platform.

For more information visit our website our social media pages:

Education:

  • B. Tech /B.E. or M.S. in Mathematics, Statistics, Analytics, Data Science, Operations Research, Decision Sciences, Computer or Information Science or other related technical or quantitative fields

Past Experience :

  • Programming skills (Python), Natural Language Processing (NLP) Techniques (like Attention mechanism, Transformer, word embedding, tokenization, RNN and so on); NLP Applications (Named Entity Recognition, Text Summarization, Dependency Parsing, etc )
  • Strong interest in researching and implementing new ML related technologies for NLP
  • Familiarity with machine learning frameworks (e.g., Tensorflow , PyTorch , keras , etc.)
  • Minimum 3 years hands-on experience in Machine Learning/ Artificial Intelligence projects, preferable to be focused on NLP
  • Experienced in Text mining and text abstraction with NLP concepts
  • Familiarity with transformer-based NLP models like BERT

Responsibilities :

  • Develop cutting edge text mining, text analytics and NLP machine learning algorithms
  • Create model comparison benchmarks and model selection processes
  • Support the engineers in model optimization and productization
  • Research and develop the NLP techniques to categorize the text data for systematic access and research and summarize the text by natural language processing
  • NLP techniques entity extraction, topic modeling, named entity recognition document understanding, object detection, computer vision, etc.
  • Progressively test and train ML capabilities to learn and adapt the best model for problem statements.
  • Work directly with data (either available data or creating sourcing/suggestion of data source) to derive actionable insights.

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