JOB DETAILS

• Data Collection and Curation.
• Select appropriate annotated datasets for Supervised Learning methods.
• Use effective text representations to transform natural language into helpful features.
• Find and implement the right algorithms and tools for NLP tasks.
• Develop ML/DL/NLP models 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.
• Building recommendation engines to increase the personalization of content for the user.
• Testing and deployment of models on cloud services i.e. AWS/GCP etc.
• Act as a bridge between product and engineering team to translate product requirements into the technical solutions.
• Stay updated and use industry best practices and latest technology trends.
• Prototype ideas rapidly using cutting edge technologies, drive architecture discussions, and proposes solutions to system and product changes.
• Deep understanding of NLP techniques for text representation, semantic extraction techniques, data structures and language modelling.
• Experience with NLP libraries and technologies including Spacy, NLTK, Gensim, Stanford NLP etc.




• Proficiency with Python and basic libraries for machine learning such as Numpy, Scikit-learn and pandas.
• Exposure to DL Model optimisation and transfer learning technique.
• Experience of cloud setting AWS/GCP, Hadoop/Spark, SQL is a plus.
• Experience with technologies like Docker, Kubernetes, CI/CD, Git is a plus.
• Experience with ML Ops is a plus.
FUNCTIONAL AREA
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