Machine Learning Engineer Job in Mantras 2 Success

Machine Learning Engineer

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Job Summary

Job Description:

Responsibilities:

Have demonstrated passion and enthusiasm for Machine Learning and Deep Learning through projects, products, etc. Ability to develop new ML/DL models from scratch.

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


Minimum qualifications:

B.Tech/M.Tech in a relevant field with 0.5-4 years experience.

We process 100s of GB of structured and unstructured data per day which is growing exponentially and with newer types of data coming in, there is a huge opportunity in terms of both business and technical aspects to grasp.

About the Data Science and Artificial Intelligence team : The team is comprised of hard working and fun-loving people with distinguished backgrounds like B.Tech/M.Tech from IITs, BITS, NITs.. In many ways, the team acts as a compass for the company and thereby a compass for the whole credit ecosystem itself. Its contributions and capabilities are recognized not only internally but also externally, with most recently receiving a patent for our NLP and AI based unstructured data processing framework(FeatGen).

Experience Required :

Minimum 1 Year

Vacancy :

2 - 4 Hires

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