Anand Ramanathan, Machine Learning Developer in Kirkland, WA, United States
Anand Ramanathan

Machine Learning Developer in Kirkland, WA, United States

Member since April 30, 2016
Anand is a machine learning engineer and entrepreneur with over 20 years at Microsoft, Amazon, and startups in roles including data scientist, engineer, and technical product manager. His expertise includes machine learning in Azure AutoML as a data scientist at Microsoft and deep learning in computer vision with 3D semantic segmentation. Anand has strong Python experience, both experimenting in Jupyter Notebooks and building robust, test-driven production quality software.
Anand is now available for hire


  • MLAI, LLC.
    Natural Language Processing (NLP), Python 3, Flask, JavaScript, JSX, SpaCy...
  • Microsoft
    R, Microsoft Power BI, Matplotlib, Scikit-learn, AutoML, Azure, Jupyter...
  • Meon
    Heroku, PostgreSQL, Ruby on Rails (RoR), Ruby, SaaS, RESTful Development...



Kirkland, WA, United States



Preferred Environment

Python, Jupyter, Flask, React, Scikit-learn, PyTorch

The most amazing...

...web-based experience I built end-to-end was Ganglion, a web app that empowers consumers to control what news they read without giving up their privacy.


  • Founder/Engineer/ML

    2020 - PRESENT
    MLAI, LLC.
    • Conceived, designed, and built an end-to-end web app.
    • Automated the daily refresh of news content enabling the entire app to work on autopilot.
    • Manually labeled data to train a model for clickbait detection in news articles with 83% accuracy.
    • Optimized the performance to efficiently fetch around 5,000 distinct news articles every day from 400 news feeds.
    • Fetched and parsed news articles daily, updated models and predictions and uploaded an optimized view to AWS S3.
    Technologies: Natural Language Processing (NLP), Python 3, Flask, JavaScript, JSX, SpaCy, Bootstrap, RSS Feeds, JSON REST APIs, SaaS, Machine Learning, Exploratory Data Analysis, Pandas, Amazon Web Services (AWS), RESTful Development, RESTful APIs, SQL, Python, Statistical Learning, Deep Learning, NumPy, Data Science, REST,, React, Full-stack, Visual Studio Code, PostgreSQL, Seaborn, Keras, Deep Neural Networks, Algorithms, Mac OS, Heroku, APIs, Architecture, Artificial Neural Networks (ANN), Sentiment Analysis, Matplotlib, Scikit-learn, SciPy, Systems, Neural Networks, NLTK, Gensim, Semantic Analysis, Tf-idf, REST APIs
  • Data Scientist

    2018 - 2020
    • Built models to evaluate over 100 datasets to discover methods to improve the AutoML library.
    • Improved the product on the benchmark against the competition by investigating and explaining a competing AutoML product's scoring methodology for imbalanced multi-class classification. I did this by digging deep into how metrics were computed.
    • Analyzed feature importances by training over 100 datasets with automatic feature engineering libraries to prioritize featurizers for our AutoML product.
    • Developed an end-to-end AutoML framework as part of a Hackathon project to understand what approaches would work best for AutoML.
    • Delivered a dataset analysis and onboarding tool, which enabled evaluating, filtering, cleaning, and onboarding of 20 datasets into our benchmarking corpus.
    • Built better compete performance graphs to improve confidence in the performance of each competitor across a corpus of over 100 datasets.
    • Identified gaps in our benchmarking dataset corpus distribution and added over 20 datasets to fill those gaps.
    Technologies: R, Microsoft Power BI, Matplotlib, Scikit-learn, AutoML, Azure, Jupyter, Pandas, NumPy, Python, JSON REST APIs, REST APIs, SaaS, Machine Learning, Exploratory Data Analysis, Python 3, RESTful Development, RESTful APIs, Docker, SQL, Statistical Learning, Deep Learning, Data Science, Visual Studio Code, Artificial Intelligence (AI), Seaborn, Azure IaaS, TensorFlow, Keras, Algorithms, Linux, Windows, APIs, Architecture, Artificial Neural Networks (ANN), SciPy, Tidyverse, Ggplot2, Systems, Neural Networks, Microsoft Azure Machine Learning (ML), Flask, Agile
  • Founder

    2015 - 2019
    • Built a web platform that allows you to create apps in minutes (https:.// .
    • Built 80 varied apps in two days.
    • Built apps for various clients on the platform.
    • Added capabilities for both general users and developers to build apps.
    • Enabled apps to be hosted as soon as built.
    Technologies: Heroku, PostgreSQL, Ruby on Rails (RoR), Ruby, SaaS, RESTful Development, RESTful APIs, jQuery, JavaScript, SQL, REST, Full-stack, Visual Studio Code, Algorithms, Linux, Mac OS, Java, APIs, Architecture, Systems, REST APIs
  • Senior Software Engineer

    2017 - 2018
    Divensi, Inc.
    • Researched and developed a deep learning model for 3D point cloud semantic segmentation of imbalanced outdoor Lidar data, with near state-of-the-art results for outdoor Lidar.
    • Developed a V1 cloud-hosted decision support system web application utilized by several enterprise users for a remote startup client. Hired a technical team and transitioned the product. Offered a CTO position by the client CEO.
    • Built a data pipeline framework for machine learning experimentation with Lidar data.
    Technologies: PDAL, Laspy, LiDAR, Jupyter, TensorFlow, Python, JSON REST APIs, Machine Learning, Exploratory Data Analysis, Python 3, Pandas, RESTful Development, RESTful APIs, JavaScript, Google Cloud Platform (GCP), SQL, Deep Learning, Statistical Learning, NumPy, Data Science, REST,, Full-stack, PostgreSQL, Artificial Intelligence (AI), Computer Vision, Keras, Django, Django REST Framework, Deep Neural Networks, Algorithms, Mac OS, APIs, Architecture, Artificial Neural Networks (ANN), Image Recognition, Matplotlib, Scikit-learn, Convolutional Neural Networks, SciPy, Systems, Neural Networks, Agile, REST APIs
  • Indie Developer

    2012 - 2014
    Independent Educational Mobile Game Developer
    • Built nine educational games released to the App Store; iOS and cross-platform using Corona SDK.
    • Saw over 30,000 downloads across games. Performed App Store optimization to maximize adoption.
    • Developed a broad range of games, from running quizzes to new mathematical puzzles. The samurai game was highly appreciated by middle school teachers in the US.
    Technologies: ASP.NET, Corona SDK, Objective-C, REST APIs, SQL, iOS, Algorithms, Mac OS, Architecture, iOS architecture, Systems
  • Founder

    2009 - 2011
    Thouwords, LLC.
    • Built a web application to make a textual website more visual by performing topic modeling with Alchemy API. Obtained images for each topic from Wikipedia APIs.
    • Created a Wikipedia visual navigator using topic modeling and Wikipedia API to get images.
    • Developed a web application to create rich ebooks for kids using pictures, video, and text books. The application was used to create picture books for kids and shared with parents.
    Technologies: AlchemyAPI, ASP.NET, Machine Learning, JavaScript, SQL, Statistical Learning, Algorithms, SOA, APIs, Architecture, Sentiment Analysis, Systems, Semantic Analysis, REST APIs
  • Senior technical program manager

    2000 - 2009
    • Built BizTalk Server, an enterprise messaging and workflow platform from idea to product.
    • Released three versions of BizTalk Server.
    • Created the first .NET based Outlook API.
    • Built a service delivery platform for mobile telecom providers using .NET and SOA, including several WS- standards like WS-reliability and WS-eventing.
    • Defined and led the inclusion of REST API in .NET WCF.
    Technologies: Windows Communication Framework (WCF), SOA, Outlook, BizTalk Server, .NET, JSON REST APIs, SDKs, SQL, REST, C++, Algorithms, Windows, ASP.NET, C#, APIs, Architecture, Systems, Workflow, RSS Feeds, Agile, REST APIs
  • Technical Product and Program Manager

    2006 - 2007
    • Captured the end-to-end Amazon retail messaging and workflow blueprint by collaborating with over 40 teams at Amazon that used the messaging and workflow framework.
    • Defined and led the creation of an internal distributed configuration store modeled on DNS.
    • Proposed a well-received vision for (the then new) Amazon cloud. It was based on true elasticity and automatic scalability.
    • Acting upon the vice president's suggestion, I presented the proposal to a special future architecture group. They incorporated it into their plans.
    • Drove the adoption of a distributed configuration store across teams in the company.
    Technologies: Java, Workflow, Engineering, SDKs, SaaS, Amazon Web Services (AWS), RESTful APIs, RESTful Development, SQL, C++, Algorithms, APIs, Architecture
  • Senior Software Engineer

    1998 - 2000
    Microsoft (via Aditi)
    • Built a code profiler for Visual Studio Internal tools in C++.
    • Developed an XSD (XML Schema Definition) library in C++.
    • Created a persistence layer for an XSLT based BizTalk schema mapper.
    • Ported FrontPage server extensions to a pre-release version of C#.
    Technologies: Profiling, CODE, Visual Studio, XSLT, XSD, XML, ATL, C++, SQL, Algorithms, Windows, ASP.NET, .NET, C#, APIs, Architecture, Systems


  • Ganglion

    A web application that empowers consumers to manage their news consumption experience providing full control and complete privacy.

    I conceived, designed, built, and deployed this project end-to-end and automated the daily refresh of news content, updating machine learning models and word cloud images of the most common news topics. This set up the entire app to work on autopilot.

    I optimized the performance to efficiently fetch approximately 5,000 distinct news articles every day from 400 news feeds and manually labeled data to train a model for clickbait detection in news articles with 83% accuracy. I trained and updated models to detect sentiment, objectivity, infer which articles have clickbait headings, perform NER, and generate word clouds. I fetched and parsed news articles daily, updated and generated models and document embeddings, created word cloud images, and uploaded to AWS S3 runs within hours.

  • AutoML

    This is an automated machine learning framework in Microsoft Azure. I was the data scientist on this team, improving the automated machine learning performance by running ML on a large corpus of benchmark datasets, and identifying ways to improve our ML pipeline.

  • Meon - Web Platform That Creates Apps in Minutes

    This is a Ruby on Rails-based web app that creates a wide variety of apps and starts using them immediately-in minutes. I conceived, designed, and built this product entirely on my own. I created 85 apps from a wide range of domains on this platform in just two days. Using this product, I built business apps for various early clients. The video below shows a tour of the variety of apps created in Meon, most of them in less than five minutes.

  • An AI Web App

    An AI web app with a complex data model designed and built for a client of my employer. It was built using Python, Django, Django Rest Framework, TypeScript, Angular and deployed to Google Cloud Platform (GCP).

  • Sumurai

    Sumurai is a math puzzle game conceived, designed, and implemented by me in 2016. It enabled young kids to learn arithmetic by playing a challenging puzzle game. I collaborated with researchers, educators, and customers to improve the game. It received great feedback from researchers and teachers in the US who used it with their students.

  • Smart Run

    An iOS educational game I designed, built, launched, and marketed. It merged an educational experience with a fast-paced running game. It was designed to add more educational content without modifying the core game code.


  • Languages

    Ruby, Python 3, Python, SQL, JavaScript, Objective-C, C#, Java, XML, XSD, XSLT, TypeScript, Lua, R, C++
  • Frameworks

    Ruby on Rails (RoR), Corona SDK, ASP.NET, .NET, Windows Communication Framework (WCF), CODE, Flask, Bootstrap, Angular, AngularJS, Unity, Cocos3d, Django, Django REST Framework
  • Libraries/APIs

    REST APIs, Pandas, Matplotlib, NLTK, SpaCy, NumPy, Scikit-learn,, TensorFlow, SciPy, ATL, LSTM, OpenCV, React, jQuery, Django ORM, Keras, Tidyverse, Ggplot2, PyTorch
  • Tools

    AutoML, Gensim, Seaborn, Microsoft Power BI, Jupyter, Visual Studio, JSX, NER, Trello, H2O AutoML
  • Paradigms

    REST, Agile, RESTful Development, Data Science, SOA
  • Other

    Algorithms, SaaS, RESTful APIs, Computer Vision, Machine Learning, Artificial Intelligence (AI), Exploratory Data Analysis, APIs, Natural Language Processing (NLP), Architecture, Artificial Neural Networks (ANN), Image Recognition, Sentiment Analysis, Microsoft Azure Machine Learning (ML), JSON REST APIs, SDKs, Deep Learning, Statistical Learning, Laspy, PDAL, AlchemyAPI, BizTalk Server, Outlook, Systems, Engineering, Workflow, Profiling, Convolutional Neural Networks, Deep Neural Networks, Neural Networks, Data Structures, RNN, Recurrent Neural Networks, Gated Recurrent Unit (GRU), Sequence Models, Hyperparameters, Regularization, iOS architecture, Semantic Analysis, Rankings, Tf-idf, RSS Feeds, Discrete Mathematics, Graph Theory, Games, 2D Games, Mathematics, Game Art, App Store Optimization, LiDAR, Full-stack
  • Platforms

    Google Cloud Platform (GCP), Visual Studio Code, Amazon Web Services (AWS), Azure IaaS, Linux, Windows, Mac OS, Heroku, iOS, Docker, Azure
  • Storage



  • Bachelor's degree in Engineering
    1990 - 1994
    Indian Institute of Technology - Roorkee India


  • Discrete Mathematics and Analyzing Social Graphs
    Higher School of Economics, National Research University/Coursera
  • Natural Language Processing with Classification and Vector Spaces
    JUNE 2020 - PRESENT
  • Natural Language Processing with Probabilistic Models
    JUNE 2020 - PRESENT
  • Mathematics for Machine Learning: Linear Algebra
    MAY 2020 - PRESENT
    Imperial College London with Coursera
  • Data Structures
    APRIL 2020 - PRESENT
    UC SanDiego/Coursera
  • Data Structures
    APRIL 2020 - PRESENT
    UC San Diego and HSE (via Coursera)
  • Algorithmic Toolbox
    MARCH 2020 - PRESENT
    UC SanDiego/Coursera
  • Algorithmic Toolbox
    MARCH 2020 - PRESENT
    UC San Diego and HSE (via Coursera)
  • Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
    MAY 2018 - PRESENT
  • Sequence Models
    MAY 2018 - PRESENT
  • Convolutional Neural Networks
    MAY 2018 - PRESENT
  • Neural Networks and Deep Learning
    MAY 2018 - PRESENT
  • Structuring Machine Learning Projects
    MAY 2018 - PRESENT
  • Deep Learning Specialization (Six courses)
    MAY 2018 - PRESENT
  • Statistical Learning
    Stanford Online
  • Introduction to Mathematical Thinking
    Stanford (via Coursera)
  • Human Computer Interaction
    JUNE 2013 - PRESENT
    UC San Diego (via Coursera)

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