AI Researcher

7 days ago

Mumbai, Maharashtra, India Zigsaw Full time ₹ 12,00,000 - ₹ 36,00,000 per year
Company Overview: Zigsaw is a leading company in the AI industry, specializing in OCR and NLP technologies. With a team of highly skilled professionals, Zigsaw aims to provide innovative solutions to its clients in Mumbai and beyond.
Role and Responsibilities:
  • Research and develop AI and Deep Learning algorithms
  • Research, evaluate, design, develop, implement, and optimize machine learning and deep learning models responsible for running NLP systems
  • Collect and process large-scale datasets to create robust, secure, and efficient NLP systems
  • Use effective text representation and classification techniques to train and evaluate models
  • Find and implement the right algorithms and tools for NLP tasks
  • Train the developed model and run evaluation experiments
  • Gather and process raw data at scale, including web scraping and data extraction
Candidate Qualifications:
  • 1-1.5 years of experience in AI, ML, and DL methods
  • Proficiency in Python and relevant tools/languages (such as Sklearn/Pandas/Numpy, Pytorch/Tensorflow)
  • Good understanding of data structures, data modeling, and software architecture
  • Experience in feature engineering and data wrangling
  • Knowledge of neural network architecture and deep learning libraries (Keras, Tensorflow, Pytorch)
  • Experience in NLP or Machine Learning libraries (NLTK, Tensorflow, Theano, Keras, Pytorch, Numpy, Scipy, Pandas, Matplotlib, Scikit-learn)
  • Familiarity with modern statistical modeling and optimization methodologies
  • Excellent coding skills and ability to write clean and testable code
  • Strong verbal and written communication skills
Required Skills:
  • Theoretical and practical knowledge of AI, ML, and DL methods
  • Experience with Python, Sklearn/Pandas/Numpy, Pytorch/Tensorflow
  • Experience with NLP or Machine Learning libraries (NLTK, Tensorflow, Theano, Keras, Pytorch, Numpy, Scipy, Pandas, Matplotlib, Scikit-learn)
  • Knowledge of neural network architecture and deep learning libraries (Keras, Tensorflow, Pytorch)
  • Good understanding of data structures, data modeling, and software architecture

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