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Machine Learning | Ex-Meta | Instagram | NYU
AI is analyzing your overall score…
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Experienced Machine learning engineer at Facebook with 8+ years experience building classification models to detect misinformation and scalable recommendation systems for Ads. Proficient in Python, SQL, Pytorch & Sci-kit learn.
New York University
Master’s Degree, Computer Science
August 1, 2015 – May 1, 2017
Anna University Chennai
Graduate Degree, Computer Science
N/A – Present
Indian Institute of Management Bangalore
Finance
N/A – Present
Airbnb
Machine Learning Engineer
February 1, 2025 – Present
Roblox
Machine Learning Engineer
April 1, 2023 – February 1, 2025
San Mateo County, California, United States · Hybrid
Machine Learning Engineer
January 1, 2020 – January 1, 2023
Software Engineer - Machine Learning
June 1, 2017 – March 1, 2020
Menlo Park, CA
Morgan Stanley
Software Intern
June 1, 2016 – August 1, 2016
Greater New York City Area
Duferco
Commodities Trading
June 1, 2012 – April 1, 2015
Switzerland
Indian Institute of Technology, Madras
Research Fellow
December 1, 2009 – May 1, 2010
Chennai Area, India
Recurrent Neural Networks for Natural language processing tasks
November 1, 2016 – Present
Trained Sequence classifiers with LSTM Recurrent Neural networks and Bi-directional LSTM to classify part of speech tags and proper names. Trained a Skip-gram based model with negative sampling to learn vector representations for words called Word embeddings in Tensorflow. Used Tensorflow, Keras.
Deep generative models for Data Augmentation
September 1, 2016 – Present
Explored Generative adversarial networks, Variational auto-encoders for Data augmentation tasks in Classification.
Steering angle prediction for Self Driving cars using Deep learning
September 1, 2016 – Present
Trained some CNN's, Resnets and experimented with RNN's to predict the steering angle given a sequence of image frames from a front-facing camera mounted on a self driving car. Used Torch for implementation
Interpreter in O-Caml (Objective caml - A functional programming language)
May 1, 2016 – Present
Developed an interpreter in OCaml for a Javascript like programming language. Developed OCaml modules for lexer, parser, abstract syntax tree builder, semantic checker and implemented transitional semantics.
Text based Sarcasm detection using semi-supervised learning and Natural language processing
May 1, 2016 – Present
Researched on an open problem in Natural language processing: “Sarcasm detection from text”. Identified patterns and used lexical cues and sentiments as predictive features in a weighted k-means nearest neighbor algorithm to classify sarcastic text.
Image based calorie estimation using Supervised learning and Neural networks
April 1, 2016 – Present
Developed a machine learning system which estimates the calorie amount of food items represented by an image. Featurized the image data with SIFT, SURF and Local binary patterns. UsedSVM withRBF kernels,boosting techniques and neural networks for detecting images.
Distributed Question Answering system using NLP
September 1, 2015 – December 1, 2015
Built a Distributed Question Answering system using Hadoop and NLP. Query/Answer processing done using part of speech tagging, Named entity recognition from NLTK library in python. Passage retrieval used Hadoop map reduce and Pig custom UDF's to extract plain-text from WikiPedia XML dumps and store in Pig table for faster access. Used Map reduce technologies like Hadoop/Pig/HBase to retrieve knowledge base, query Question, Score and rank possible answer passages.
Porta Via - Food delivery & Takeout android app
June 1, 2015 – July 1, 2015
Designed a food delivery store locator streamed from Yelp API and Locu API data using Angular JS & Google Maps API , and developed an order management module in Java. The android version of the app is available at google play store (https://play.google.com/store/apps/details?id=app.com.example.android.yelpdelivery)
Data Analytics in Retail
September 1, 2011 – December 1, 2011
Consulted ‘Fab India’ - an Indian ethnic wear retailer. Derived useful business insights from their Annual Sales data. Recommended merchandising and clustering strategies based on statistical analysis of FabIndia's sales data
Modeling derivative instruments to hedge macroeconomic shocks
June 1, 2011 – September 1, 2011
Recommended Plain Vanilla and Exotic Option Strategies to hedge macro shocks like Inflation Risk, Oil Shocks, FX risks
Intuitive & Predictive MathML editor
May 1, 2008 – November 1, 2008
Developed an editor for implementing the MathML standard for representing Mathematics in Web using Adobe Flex, Actionscript 3 and Java. The Components include a WYSIWYG editor, MathML equation parser and ren- derer, Intuitive Help Assistant, Equation Editing, Server Support and Usability features. The tool was developed for Heymath’s Math content editors. Technolo- gies( Java, Flex Action script 3, Mysql,XML)
Play with trees
May 1, 2008 – July 1, 2008
Developed a simulation of a File Directory Structure similar to the windows explorer . The project was done using Java Servlets, MySql, and external javascript librairies Yahoo User Interface Tree View Control and EXT JS.
Cultural Fit Analysis
The candidate has a diverse project portfolio spanning various ML applications, functional programming, and even finance, indicating intellectual curiosity and a broad skill set. Their experience at major tech companies aligns well with a fast-paced, innovation-driven culture. The transition from commodities trading to ML engineering demonstrates significant career pivot and adaptability, suggesting a proactive and growth-oriented mindset. However, the lack of explicit team-based project descriptions makes it hard to fully assess collaborative cultural fit.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong problem-solving orientation and a research-driven approach, which are valuable for senior ML roles. The breadth of projects suggests adaptability and a willingness to explore diverse technical challenges. However, without specific behavioral assessment data, it's difficult to fully assess collaboration, stress handling, or leadership potential.