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About Me
I am a Software Development Engineer with about 4 years of experience in Designing, Developing and Maintaining scalable software. I have worked in the fields of Machine Le... scalable software. I have worked in the fields of Machine Learning, Artificial Intelligence and Web development. I also have experience in System Design and microservices. I have worked on projects for a myriad of clients some of which are State Bank of India, GoDaddy, eBay India, Anarock and more.
Some of the programming languages and frameworks I am proficient are: Python, Rust, JavaScript(Backend and Frontend), C++, Tensorflow, Amazon Web Services etc.
I have also worked on setting up infrastructure using Ansible, worked on setting up CI/CD pipelines integrating services like Nagios etc.
In my free time, you can find me working on Open-source projects and learning new technologies and algorithms.
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Skills
Positions
Portfolio Projects
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I identified the problem. Designed and developed related services. Performed testing and deployed the services.
Description
Determining Users' access to various digital artifacts is a canonical problem in a large scale enterprise system.
Developing a consistent role-based access control as a service with consistency, scale and, performance in mind. The application supports managing various role-based hierarchies with support for grouping and aggregation of resources.
Writing the service primarily in Rust Programming Language.
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I was responsible for designing and development of the algorithm. I also gave a seminar on the same.
Description
The algorithm is used for multi-agent path planning. The algorithm is much faster due to its asynchronous nature. Due to its decentralized and state aware nature, it can be used in a wide variety of environments. This empowers complete autonomy for several AI-based robots.'
Implemented and demonstrated the algorithm in Java.
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I headed a team of 4 to implement the project. I was also directly responsible for the implementation and testing of the project.
Description
Implemented the Support Vector Machine Algorithm in Python. Aggregated and cleaned the data for the application. Integrated the algorithms with ElasticSearch, Logstash and, Kibanna for real-time monitoring. Achieved an Accuracy of 96%.
Won the runner-up prize in PICT's Impetus and Concepts 2017 competition.
Implemented in Python