
Software Engineer, ML at Meta
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Assessing your cultural and operational fit
Gaining professional experience in the field of AI & Machine Learning by working on excellent projects with amazing people. I believe in making an impact and achieving goals through perseverance, optimism, productive teamwork and creativity.
Rensselaer Polytechnic Institute
Master of Science (MS), Information Technology
January 1, 2016 – January 1, 2017
Manipal Institute of Technology
Bachelor of Technology (B.Tech.), Electrical, Electronics and Communications Engineering
January 1, 2012 – January 1, 2016
Meta
Software Engineer, ML
March 1, 2022 – Present
New York City Metropolitan Area
IBM
Advisory Software Engineer
September 1, 2020 – April 1, 2022
IBM
Machine Learning Software Engineer
March 1, 2018 – September 1, 2020
IBM
Machine Learning Intern
May 1, 2017 – August 1, 2017
Greater Delhi Area
Rensselaer Polytechnic Institute
Graduate Teaching Assistant
August 1, 2016 – May 1, 2017
Albany, New York Metropolitan Area
Bosch Engineering and Business Solutions
Technical Intern
January 1, 2016 – June 1, 2016
Bengaluru, Karnataka, India
VE Commercial Vehicles Limited (A Volvo Group and Eicher Motors Joint Venture)
Summer Intern
June 1, 2015 – July 1, 2015
Greater Indore Area
Movie Recommendation System
March 1, 2017 – May 1, 2017
Developed a movie recommender system using multiple movie data sources in R, to predict the ratings provided by a user to a new movie. Quantitative analysis of the data was done to understand the user behavior. Used classification algorithms with optimizations and cross validation to predict ratings accurately.
Integrated Secure Mobile Application Development (Deloitte)
January 1, 2017 – May 1, 2017
Capstone project: Our team of 4 worked in collaboration with Deloitte to develop an end-to-end security framework for Enterprise Mobility solutions with a focus on technical functionality and usability. Worked alongside Deloitte to understand the project requirements and provided detailed visual presentations and documentation at the end of the project.
Predicting user’s first booking on Airbnb website
October 1, 2016 – December 1, 2016
Predicted top 5 countries a user will book for the first time on Airbnb with a top 10% score on Kaggle.com. Used 3 different machine learning algorithms (Random forest, K nearest neighbours and gradient boosting) to provide improved accuracy
PocketChef Android Application
August 1, 2016 – November 1, 2016
Developed a recipe suggestion and kitchen inventory management android application for students and other amateurs that gives customized recipe based on user’s available ingredients. Integrated the Food2Fork API into the app using Java and worked on the database creation over web server. Designed and documented the entire development process using Agile and Scrum methodology.
IBM Developer Jumpstart - Practitioner
IBM
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
DeepLearning.AI
June 24, 2026 – Present
Structuring Machine Learning Projects
DeepLearning.AI
June 24, 2026 – Present
Neural Networks and Deep Learning
DeepLearning.AI
June 24, 2026 – Present
Algorithm Toolbox
UC San Diego
June 24, 2026 – Present
Nettech Certification for Networking
Nettech Private Limited
June 24, 2026 – Present
First Patent File
IBM
June 24, 2026 – Present
Sequence Models
DeepLearning.AI
June 24, 2026 – Present
IBM AI Skills Academy Deep Learning Practitioner
IBM
June 24, 2026 – Present
Deep Learning Specialization
DeepLearning.AI
June 24, 2026 – Present
Convolutional Neural Networks
DeepLearning.AI
June 24, 2026 – Present
IBM AI Skills Academy Deep Learning Explorer
IBM
June 24, 2026 – Present
Data Structures
UC San Diego
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from mobile app development to machine learning competitions and industry collaborations, indicates adaptability and a broad interest in technology. Their experience at major tech companies like IBM and Meta, coupled with academic pursuits, suggests a drive for continuous learning and professional growth. The transition from Software Engineer, ML to a Data Analyst target role aligns with their strong data analysis and ML background, indicating a focused career direction. The breadth of skills and exposure to different problem domains (e.g., IoT, Ads Ranking, AI models) suggests a good cultural fit for dynamic and innovative environments.
Soft Skills & Operational Fit
The candidate's project descriptions indicate experience in team collaboration (Deloitte capstone), agile methodologies (PocketChef), and presenting technical information. Their roles at IBM and Meta suggest an ability to work in complex, large-scale environments and contribute to building engineering cultures. The teaching assistant role also implies communication and mentorship skills. However, without specific psychometric test results, a definitive assessment of operational fit and stress handling is not possible.