Qualifications: BS/MS in a relevant field with 2-5 years' experience. Or PhD in a relevant field with 0-3 years' experience.
Have demonstrated passion and enthusiasm for Machine Learning and Deep Learning through projects, products, etc.
Ability to develop new ML/DL models from scratch.
Hands-on experience with Tensorflow, Keras/PyTorch, scikit-learn, etc. with ability to create, analyse and experiment with new deep neural network architectures and work on large datasets.
Keep up-to-date with the advances in neural networks and particularly their applications to NLP problems.
Be sharp at Algorithm Design and Complexity Analysis, solving new problems with ease with effective and computationally efficient methods.
Enjoy programming and be comfortable with one or more languages such as, C, C++, Java, Scala, and Python.
Eager to quickly learn new concepts, languages, tools and technologies as required, for example, the credit underwriting fundamentals or new deep learning frameworks.
Enjoy building products that are generic and can cater to multiple tenants, through appropriate parameterization/abstraction.
Be ready to work on distributed programming and big data frameworks such as Spark and optimize the performance on multiple nodes.
Be excited to work in a startup environment and take end-to-end responsibilities working with the co-team members.