Help & Supportcareers@gravityer.com
Technical lead at HubSpot
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
My interests are Software Development, Machine/Deep learning and Natural Language Processing. I have 4 years of industrial experience in software development in Retail and Health Care industries. I have good understanding of ML algorithms like SVM, Decision trees, Regression, Neural Networks etc. and experience in applying them to solve practical problems in the areas of Computer Vision and NLP. I have good experience using frameworks like DL4J, Keras, Tensor flow, Apache Spark along with NoSQL databases like Redis, Couch DB and MongoDB for Machine/Deep Learning Projects. Also, experienced in Spring Boot.
Ohio University
Master's degree, Computer Science
January 1, 2014 – December 1, 2016
Amrita School of Engineering, Coimbatore
Bachelor of Technology (BTech), Computer Science
January 1, 2008 – January 1, 2012
HubSpot
Technical Lead
August 1, 2022 – Present
HubSpot
Senior Software Engineer II
November 1, 2021 – July 1, 2022
Strategic Solutions Group (SSG)
Senior Software Engineer
January 1, 2017 – October 1, 2021
Needham, MA
Strategic Solutions Group (SSG)
Software Engineering Intern
May 1, 2016 – August 1, 2016
Needham, MA
International Space University
Technical Support Analyst
May 1, 2015 – August 1, 2015
Athens, ohio
Ohio University
Graduate Assistant
August 1, 2014 – December 1, 2016
Athens,Ohio
Cognizant Technology Solutions
Programmer Analyst
May 1, 2012 – June 1, 2014
Chennai Area, India
Authorship Attribution using NLTK
February 1, 2016 – Present
Given an unknown piece of text, this project aims to detect who could have possible written it using NLTK. I have trained trigram language models for Shakespeare, Austin and Charleston using Lidstone Smoothing and tested with data from all the 3 authors and subset of data from Bible to identify that writings in the Bible are very near to writings of the Shakespeare with perplexity of 32. I have also tried a different approach by computing the geometric mean of the singleton probabilities and the results turned out to be the same as previous approach.
Language Detection using NLTK
February 1, 2016 – Present
Given an unknown piece of text, this project aims to detect what language it belongs to, using NLTK. I have trained bigram language models at character level for 11 languages using Lidstone smoothing and tested with text from 11 languages. Upon doing a sentence level classification with evaluation metric as confusion matrix, I am able to best identify text from Greek language with 99.8% accuracy and least identifiable is Portuguese with 82% accuracy.
Sentiment Analysis using Apache Storm
June 1, 2015 – July 1, 2015
Analyzed real time twitter feed having ISU and SSP'15 related hash tags using Apache Storm and MongoDB for sentiment analysis task.
Tag Suggestion for Stackoverflow.com Questions
April 1, 2015 – Present
Designed, implemented and tested Supervised and Un-Supervised Machine Learning models using Support Vector Machines and Clustering respectively to suggest tags with at least 83% accuracy while a question is being asked at Stackoverflow.com
Digit Recognition
March 1, 2015 – Present
The project aims at implementing 4 different versions of Perceptron and evaluating it for thorough comparison with Kernel and non-Kernel versions of SVM on Handwritten Digit Recognition data set using one-vs-all binary classification technique.
Query Processing Engine using JSQL Parser
May 1, 2014 – June 1, 2014
Designed and developed a query processing engine using JSQL Parser to transform the given SQL query into an efficient low level query to read and analyze the flat file data.
Search Engine Using Apache Lucene 4.0
February 1, 2014 – April 1, 2014
Used Apache Lucene 4.0 to design a search application to index the failed SAP iDoc’s at Message Broker level for an easy and fast access to reprocess them.
Monitoring Portal using IBM MQ Java library
November 1, 2013 – January 1, 2014
Designed and implemented a light weight, scalable and easy to use any where MQ monitoring dash board. This light weight product could replace the original IBM MQ to access all the important and critical information.
Distributed Storage Management
January 1, 2012 – April 1, 2012
Developed a user friendly application that aims in optimizing the free space utilization among the storage nodes with one node acting as a controller giving ability to the users to store/retrieve data from the distributed storage
Oracle Certified Professional, Java SE 6 Programmer
Oracle
June 24, 2026 – Present
IBM Certified Solution Developer, WebSphere Message Broker V8.0
IBM
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from machine learning to distributed systems and monitoring tools, suggests adaptability and a broad interest in technical challenges. The progression from Software Engineer to Technical Lead at HubSpot indicates a capacity for growth and taking on increased responsibility. The academic background (Master's in Computer Science) and certifications further demonstrate a commitment to continuous learning. The projects align well with a data-driven culture, showing initiative in exploring various analytical techniques.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to problem-solving and a drive to build end-to-end solutions. Experience as a Technical Lead suggests leadership and potentially strong collaboration skills. However, without specific assessment data, a definitive evaluation of soft skills and operational fit is limited.