NLP Engineer

Job brief

• NLP Engineer responsibilities include transforming natural language data into useful features using NLP techniques to feed classification algorithms.
• To succeed in this role, you should possess outstanding skills in statistical analysis, machine learning methods and text representation techniques.
• Your ultimate goal is to develop efficient self-learning NLP applications in production. 

Responsibilities

• Study and transform data science prototypes
• Design NLP tools and applications that help measure and diagnose performance issues
• Select appropriate annotated datasets for Supervised Learning methods
• Use effective text representations to transform natural language into useful features
• 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
• Explore fine-tuning methods for supervised learning
• Remain updated in the rapidly changing field of machine learning

Requirements

• 3+ years of hands-on experience in Python and developing Speech to Text (STT/ASR) systems using open source toolkits like Kaldi, Pytorch-Kaldi, Espnet andWav2letter ++                   
• Understanding of NLP techniques for text representation, semantic extraction techniques, data structures and modeling
• Hands on experience and knowledge on developing Factorized TDNN, CNN and BiLSTM based acoustic models
• Hands on experience dealing with Grapheme to phoneme Modelling, should be able to develop a G2P model for less resource languages
• Hands on experience developing statistical as well as neural language models
• Knowledge of Java and R
• Ability to write robust and testable code
• Strong communication skills
• An analytical mind with problem-solving abilities