Role Summary

  • Work on end to end data science lifecycle. from building proof of concept models to production-ready models & work with engineers to deploy them to production 
  • Execute and take ownership of deep learning projects end-to-end. Good exposure to various deep learning algorithms and framework 
  •  Should be able to effortlessly switch between roles of an individual contributor, team member, and data science manager as demanded by each project
  • Figure out gaps in existing products and add intelligence to improve it.
  • Designing the frameworks in data sciences (R, Python, Azure ML, AWS ML, Google ML, Spark etc) to be used in relevant projects 
  • Keep updated on latest research in AI and deep learning and find ways in which it can be used to solve business problems 
  • Must be able to read research papers (some novel architectures, training techniques etc and be able to implement it fully  to solve our specific problems

Essential Qualification 

Master/PhD in Quantitative & Engineering disciplines – Mathematics, Statistics, Physics, Computer Science, Electronics, and Data Mining, etc



5 years of strong experience in machine learning and 3 years of experience in production level deep learning project is a must

Technical Skills

  • Expert of Python 
  • Hands-on experience in bundling unstructured (Image, Video, Audio) and build solution using Deep Learning/ Machine Learning 
  • Experience implementing object detection, GAN’s Knowledge of reinforcement learning is a plus.
  • Good grasp and detailed knowledge of any one deep learning library (PyTorch, Tensorflow, Caffe etc.) a must
  • Experience with Data Visualization tools like Tableau, Microsoft Power BI and Sisense
  • Exposure to working on AI/ Data Science/ Analytics platforms like Microsoft AI, AWS AI, IBM WATSON, H20, Knime
  • Strong business acumen to understand business objectives & dynamics and possess excellent written and verbal communication skills for coordinating across teams
  • Experience in analyzing complex problems and translating them to data since algorithms with due attention to computational efficiency and testing at scale
  • Eхреrіеnсе in machine learning, supervised and unsupervised,
  • Classification, Data/Text Mining, NLP, Decision Trees, Adaptive Decision Algorithms, Neural Networks, Deep Learning Algorithms
  • Strong problem solving skills 


  • Fun and friendly people to work with 
  • Flexible working hours 
  • 5 Working Days
  • Festival Allowance
  • Health Insurance 
  • Fully Remote (You may need to visit the office when required)