Rahul Raghavan
ML EngineerSenior Software Engineer at Affirm
Affirm
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Senior Software Engineer at Affirm
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Senior Software engineer at Affirm
University of Maryland Baltimore County
Master of Science (M.S.), Computer Science
January 1, 2016 – January 1, 2018
University of Mumbai
Bachelor of Technology (BTech), Information Technology
January 1, 2009 – January 1, 2013
Affirm
Senior Software Engineer
January 1, 2025 – Present
Vancouver, British Columbia, Canada · Remote
Senior Software Engineer
August 1, 2021 – September 1, 2024
Vancouver, British Columbia, Canada · Hybrid
Walmart Global Tech
Senior Software Engineer
December 1, 2020 – August 1, 2021
Walmart Global Tech
Software Engineer III
August 1, 2018 – December 1, 2020
Verisk Analytics
Cognitive Analytics & Machine Learning Engineer Intern
June 1, 2017 – May 1, 2018
Jersey
University of Maryland Baltimore County
Research Assistant
January 1, 2017 – June 1, 2017
Washington DC-Baltimore Area
Inknowledge Inc.
Full Stack Developer
September 1, 2015 – June 1, 2016
Mumbai Metropolitan Region
Inknowledge Inc.
Web Development Engineer
August 1, 2014 – September 1, 2015
Mumbai Metropolitan Region
Object Detection in Images using Unlabelled Dataset
May 1, 2017 – Present
- Trained multiple object detector systems like Single Shot Detection (SSD), YOLO9000 - Generated synthetic dataset with Images using OpenCV and Annotations in absence of labeled dataset - Used transfer learning to Transfer lower level image semantics to the task of object detection - Trained the synthetic dataset using state of the art object detector systems like SSD written in Caffe - Improved the performance of the system in terms of time with the help of a more fast object detector system like YOLO9000 written using darknet framework Technologies Used : C++, Deep Learning, Unsupervised Learning, Machine Learning Computer Vision, Python
Multi Threaded Client Server Banking Application
February 1, 2017 – March 1, 2017
- This Multi threaded banking application facilitates users to perform banking transactions along with an additional feature of periodic deposits into account. - Server and client communication is effectively handled using TCP socket communication secured with POSIX's mutex locking mechanism to handle concurrent transaction requests. - Analyzed and performed Load and Performance testing for 10,30,50,100+ clients considering following parameters: 1. No. of clients versus Avg.time per transaction 2. Varying no. of clients versus Avg. time per transaction - Efficient logging enhanced tracking of every transaction details (timestamp,type of trn,status) - Technologies: C,C++,Socket programming, Python, Shell scripting.
Action Prediction in Videos using Deep Learning
January 1, 2017 – May 1, 2017
- Anticipated Visual Representation in videos, by training a Convolution Neural Network on Unlabelled Videos - Trained deep learning model on Unlabelled videos consisting of more than 600 hours of Youtube videos - Extracted visual representation from the model and added a SVM classifier at the end to predict action categories in the future Technologies Stack: Torch, Deep Learning, Computer Vision, MATLAB, Python
Novel approach to Evaluate Student performance using Data Mining
January 1, 2014 – June 1, 2014
- The primary goal of the project was to evaluate a student’s performance based on the prediction made for his marks. - First, we predicted a student’s marks for the current semester based on academic and on non-academic parameters using the One R algorithm. - Then based on the prediction, we quantified the amount of improvement needed in different parameters and how it would affect the final score of the student . - This was used to determine which parameters the student can improve on in order to increase his/her marks. - This kind of data would help educational institutes to improve their managerial decisions. - The product was developed in C# .NET which held the code for prediction and identification of strengths and weakness of a student. - The project won the third prize in the ‘MIND-SI’ project competition. Technology Stack: Data Mining, C#, SQL
Cultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards Machine Learning and Data Mining, which aligns well with an ML Engineer role. The diversity of projects, from computer vision to data mining and even a multi-threaded banking application, indicates a broad technical curiosity. However, the professional experience, while at reputable companies, primarily lists general software engineering skills (PHP, React.js, Java, MySQL) with less explicit mention of ML engineering responsibilities, which could indicate a potential gap in direct industry ML deployment experience compared to the target role. The 'Senior Software Engineer' role at Affirm with a future start date and no listed skills is not relevant for current assessment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to analyze performance (Load and Performance testing), track details (logging), and innovate (novel approach to evaluate student performance). The experience at Facebook and Walmart Global Tech suggests an ability to work in large-scale, fast-paced environments. However, specific soft skill assessments are not available in the provided data.