Anand Ramanathan, Developer in Bellevue, WA, United States
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Anand Ramanathan

Verified Expert  in Engineering

Machine Learning Developer

Location
Bellevue, WA, United States
Toptal Member Since
April 29, 2020

Anand is a leading applied scientist in LLM/GPT applications, blending engineering proficiency, product expertise, & the latest scientific insight. He has 20+ years of experience at Microsoft, Amazon, startups, & consulting. He is proficient in NLU, NLP, Python, & AI engineering. His innovative use of GPT for user-centric solutions enables him to skillfully transform complex AI technologies into efficient, practical products, consistently leading in industry advancements & setting new standards.

Portfolio

Ripcord
Generative Pre-trained Transformers (GPT), Chatbots...
MLAI, LLC.
Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT)...
Healthcare Provider Client (via Toptal)
Machine Learning, Deep Learning, Computer Vision, Healthcare...

Experience

Availability

Part-time

Preferred Environment

Python, OpenAI GPT-4 API, OpenAI Assistants API, Generative Pre-trained Transformers (GPT), Google Colaboratory (Colab), ChatGPT, GitHub Copilot Chat, GPT Builder

The most amazing...

...experience I've had (from Nov 2022 to date) is harnessing LLMs via ChatGPT and APIs—launching a v1 product to chat with documents, solving complex LLM problems.

Work Experience

Principal Machine Learning Scientist

2022 - PRESENT
Ripcord
  • Built and launched Docufai, a v1 web application to chat with documents using generative AI. I owned all aspects of the AI—from experiments and benchmarking to production AI code. Also influenced product, engineering, design, strategy, and release.
  • Added vector stores/retrieval-augmented generation (RAG) as a key component. Created an in-memory RAG index. Researched and provided several alternatives for integrating a vector store and search into existing text search databases and ecosystems.
  • Retrained a neural network with new data to split/classify and extract key value pairs from documents—from dataset creation/curation to training.
  • Reviewed and provided guidance on the training to launch the pipeline of an object detection model (YOLO-based).
  • Contributed to a human-in-the-loop AI model that provided a model-based first cut of annotations (key value pairs) in documents that were then reviewed and updated by humans.
  • Researched several ways to make LLM/GPT-based apps work correctly—hallucination reduction, suggesting questions in documents, checking AI-generated answers using AI, and more. Many of these were later validated by public external research.
  • Evaluated and implemented various strategies to deal with large and/or many documents when interacting with LLMs like ChatGPT.
  • Investigated custom GPTs and the Assistants API from OpenAI to identify how to use these in our products.
  • Researched and shortlisted transformer-based models (LayoutLM, LILT, etc.) for document layout models that incorporate computer vision and language/NLP/NLU for handling scanned documents and images containing text.
  • Evaluated and used several OCR libraries for extracting text from documents.
Technologies: Generative Pre-trained Transformers (GPT), Chatbots, Chatbot Conversation Design, Large Language Models (LLMs), Retrieval-augmented Generation (RAG), OpenAI, OpenAI GPT-4 API, OpenAI GPT-3 API, PaLM 2, Google Gecko Embeddings, Claude, LangChain, ChromaDB, Qdrant, AI Research, Research, Benchmarking, Datasets, Evaluation, Azure Machine Learning, Azure Cognitive Services, Artificial Intelligence (AI), Python 3, Python API, Vector Search, Hybrid Search, Prompt Engineering, AI Agents, Amazon Bedrock, Amazon SageMaker, Llama 2, MTEB, Large Model Systems Organization (LMSYS), OpenAI Assistants API, Google Colaboratory (Colab), Machine Learning, Deep Learning, Natural Language Processing (NLP), Full-stack, PyTorch, NumPy, Pandas, Exploratory Data Analysis, Data Science, Seaborn, Jupyter, Computer Vision, Azure IaaS, TensorFlow, Python, Google Cloud Platform (GCP), Deep Neural Networks, Algorithms, MacOS, Visual Studio Code (VS Code), PostgreSQL, APIs, Architecture, Convolutional Neural Networks (CNN), Neural Networks, Recurrent Neural Networks (RNNs), Sequence Models, Hyperparameters, Regularization, Natural Language Toolkit (NLTK), SpaCy, Named-entity Recognition (NER), Mathematics, Language Models, ChatGPT, Vector Stores, Full-stack Development, iPaaS, Generative AI, Generative Pre-trained Transformer 3 (GPT-3)

Founder | Machine Learning Engineer

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: Generative Pre-trained Transformers (GPT), 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, SQL, Python, Statistical Learning, Deep Learning, NumPy, Data Science, REST, Fast.ai, React, Full-stack, Visual Studio Code (VS Code), PostgreSQL, Seaborn, Keras, Deep Neural Networks, Algorithms, MacOS, Heroku, APIs, Architecture, Artificial Neural Networks (ANN), Sentiment Analysis, Matplotlib, Scikit-learn, SciPy, Systems, Neural Networks, Natural Language Toolkit (NLTK), Gensim, Semantic Analysis, Tf-idf, REST APIs, Web Scraping, Task Analysis, Hyperparameters, Regularization, Named-entity Recognition (NER), Mathematics, Google Colaboratory (Colab), Research, Benchmarking, Datasets, Evaluation, Python API, Full-stack Development, iPaaS, Generative AI, Generative Pre-trained Transformer 3 (GPT-3)

AI/ML Engineer

2022 - 2022
Healthcare Provider Client (via Toptal)
  • Conducted feasibility analysis of an ML model for the business problem.
  • Created estimates of data collection and annotation needed.
  • Provided candidate models to evaluate once data was available.
  • Answered all client's questions to their total satisfaction.
Technologies: Machine Learning, Deep Learning, Computer Vision, Healthcare, 3D Image Processing, Image Processing, Medical Imaging, Task Analysis, Google Colaboratory (Colab), Research, Datasets, Python API

Senior AI Engineer

2021 - 2022
RedRoute
  • Owned AI for the company; defined the AI roadmap for the company, combining several ideas from business, product, and technology as well as from academia, research, and industry.
  • Led the audio-related data science roadmap and work; mentored/technically managed an experienced audio data science researcher.
  • Built a real time audio barge-in detection model that performed very well with low resource requirements, compared to several prior attempts.
  • Improved the performance of an eCommerce intent detection model by 2-5%—analyzing and relabeling the data, manually prioritizing and labeling high impact utterances, retraining and redeploying the model, and creating and monitoring looker dashboards.
  • Increased customer handle rates by adding richer responses for eCommerce customers; this was done by answering frequently asked questions based on information from the customer's website and knowledge base. Created dashboards to monitor these changes.
  • Created a transcriber/speaker diary tool to transcribe conversations.
  • Built several dashboards and looks (queries) in Looker to monitor the impact of different changes.
  • Educated the team on Kanban and influenced the deployment of a variant of Kanban in the company.
  • Contributed to other areas of the company, including preparing to scale and establishing and improving processes and the business/sales/marketing/product strategy.
Technologies: Python, Python 3, TensorFlow, Deep Learning, Realtime, IVR, Interactive Voice Response (IVR), Dialog Systems, Amazon Web Services (AWS), Ansible, Docker, Machine Learning Operations (MLOps), Google Speech-to-Text API, Labeling, Jupyter Notebook, Jupyter, Kanban, Looker, ETL, MongoDB, Snowflake, Flask, Technical Hiring, Source Code Review, Code Review, Task Analysis, Interviewing, Team Management, Hyperparameters, Regularization, Language Models, Google Colaboratory (Colab), Chatbot Conversation Design, Chatbots, Large Language Models (LLMs), Research, Benchmarking, Datasets, Python API, Full-stack Development

Data Scientist

2018 - 2020
Microsoft
  • 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 complete 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, Docker, SQL, Statistical Learning, Deep Learning, Data Science, Visual Studio Code (VS Code), Artificial Intelligence (AI), Seaborn, Azure IaaS, TensorFlow, Keras, Algorithms, Linux, Windows, APIs, Architecture, Artificial Neural Networks (ANN), SciPy, Tidyverse, Ggplot2, Systems, Neural Networks, Azure Machine Learning, Flask, Agile, Source Code Review, Code Review, Task Analysis, Hyperparameters, Regularization, Research, Benchmarking, Datasets, Evaluation, Python API

Founder

2015 - 2019
Meon
  • Built a web platform that allows you to create apps in minutes, Meonapp.com.
  • Developed 80 apps in two days across several application domains.
  • Created apps for various clients on the platform, including a tailor management app, a music composition app.
  • Added capabilities for both general users and developers to build apps.
  • Enabled apps to be hosted as soon as built, reducing turnaround time greatly.
Technologies: Heroku, PostgreSQL, Ruby on Rails (RoR), Ruby, SaaS, RESTful Development, jQuery, JavaScript, SQL, REST, Full-stack, Visual Studio Code (VS Code), Algorithms, Linux, MacOS, Java, APIs, Architecture, Systems, REST APIs, Source Code Review, Code Review, Task Analysis, Research, Full-stack Development, iPaaS

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, JavaScript, Google Cloud Platform (GCP), SQL, Deep Learning, Statistical Learning, NumPy, Data Science, REST, Fast.ai, Full-stack, PostgreSQL, Artificial Intelligence (AI), Computer Vision, Keras, Django, Django REST Framework, Deep Neural Networks, Algorithms, MacOS, APIs, Architecture, Artificial Neural Networks (ANN), Image Recognition, Matplotlib, Scikit-learn, Convolutional Neural Networks (CNN), SciPy, Systems, Neural Networks, Agile, REST APIs, 3D Image Processing, Image Processing, Technical Hiring, Source Code Review, Code Review, Task Analysis, Interviewing, Team Management, Mathematics, Research, Datasets, Evaluation, Python API, Full-stack Development, iPaaS

Freelance Developer

2012 - 2014
Self Employment
  • Built nine educational games that were released to the App Store; iOS and cross-platform using the Corona SDK.
  • Performed App Store optimization to maximize adoption and saw over 30,000 downloads across games.
  • 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, MacOS, Architecture, Systems, Task Analysis, Full-stack Development

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, Service-oriented Architecture (SOA), APIs, Architecture, Sentiment Analysis, Systems, Semantic Analysis, REST APIs, Technical Hiring, Source Code Review, Code Review, Task Analysis, Interviewing, Team Management, Research, Full-stack Development, iPaaS

Senior Technical Program Manager

2000 - 2009
Microsoft
  • 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, and released two versions of it.
  • 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 the REST API in .NET WCF.
Technologies: Windows Communication Foundation (WCF), Service-oriented Architecture (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, ETL, Technical Hiring, Task Analysis, Interviewing, Team Management, Research

Technical Product and Program Manager

2006 - 2007
Amazon
  • 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.
  • Presented the proposal to a special future architecture group, acting upon the vice president's suggestion. 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), REST APIs, RESTful Development, SQL, C++, Algorithms, APIs, Architecture, Technical Hiring, Task Analysis, Interviewing

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 the 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, Technical Hiring, Source Code Review, Code Review, Task Analysis, Interviewing, Team Management

Ganglion

https://www.ganglion.me
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

https://azure.microsoft.com/en-us/services/machine-learning/automatedml/
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

https://youtu.be/ZCM7V_QH1zk
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, and Angular; it was deployed to Google Cloud Platform (GCP).

Sumurai

https://www.quora.com/Which-android-games-make-you-smarter
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.
1990 - 1994

Bachelor's Degree in Engineering

Indian Institute of Technology - Roorkee, India

MAY 2022 - PRESENT

Fundamentals of Reinforcement Learning

University of Alberta | via Coursera

APRIL 2022 - PRESENT

TensorFlow Developer Certificate

DeepLearning.AI

APRIL 2022 - PRESENT

DeepLearning.AI TensorFlow Certification

Coursera

JANUARY 2022 - PRESENT

Cryptocurrency Forecasting Using Machine Learning in Power BI

Coursera

FEBRUARY 2021 - PRESENT

Discrete Mathematics and Analyzing Social Graphs

Higher School of Economics, National Research University | via Coursera

JUNE 2020 - PRESENT

Natural Language Processing with Classification and Vector Spaces

DeepLearning.AI | via Coursera

JUNE 2020 - PRESENT

Natural Language Processing with Probabilistic Models

DeepLearning.AI | via Coursera

MAY 2020 - PRESENT

Mathematics for Machine Learning: Linear Algebra

Imperial College London | via Coursera

APRIL 2020 - PRESENT

Data Structures

UC San Diego | via Coursera

APRIL 2020 - PRESENT

Data Structures

UC San Diego and HSE | via Coursera

MARCH 2020 - PRESENT

Algorithmic Toolbox

UC San Diego | via Coursera

MARCH 2020 - PRESENT

Algorithmic Toolbox

UC San Diego and HSE | via Coursera

MAY 2018 - PRESENT

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

DeepLearning.AI | via Coursera

MAY 2018 - PRESENT

Sequence Models

DeepLearning.AI | via Coursera

MAY 2018 - PRESENT

Convolutional Neural Networks

DeepLearning.AI | via Coursera

MAY 2018 - PRESENT

Neural Networks and Deep Learning

DeepLearning.AI | via Coursera

MAY 2018 - PRESENT

Structuring Machine Learning Projects

DeepLearning.AI | via Coursera

MAY 2018 - PRESENT

Deep Learning Specialization (Six courses)

DeepLearning.AI | via Coursera

AUGUST 2016 - PRESENT

Statistical Learning

Stanford Online

NOVEMBER 2015 - PRESENT

Introduction to Mathematical Thinking

Stanford | via Coursera

JUNE 2013 - PRESENT

Human Computer Interaction

UC San Diego | via Coursera

Libraries/APIs

REST APIs, Pandas, Matplotlib, Natural Language Toolkit (NLTK), SpaCy, NumPy, Scikit-learn, Fast.ai, PyTorch, TensorFlow, OpenAI Assistants API, SciPy, ATL, LSTM, OpenCV, React, jQuery, Django ORM, Keras, Tidyverse, Ggplot2, Google Speech-to-Text API, Azure Cognitive Services, Python API

Tools

AutoML, ChatGPT, Azure Machine Learning, Gensim, Seaborn, Microsoft Power BI, Jupyter, Visual Studio, JSX, Named-entity Recognition (NER), Trello, H2O AutoML, Ansible, Looker, Amazon SageMaker, GPT Builder

Frameworks

Ruby on Rails (RoR), Flask, Corona SDK, ASP.NET, .NET, CODE, Bootstrap, Angular, AngularJS, Unity, Cocos3d, Django, Django REST Framework, Realtime

Languages

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

Paradigms

REST, Agile, RESTful Development, Data Science, ETL, Service-oriented Architecture (SOA), App Store Optimization (ASO), Kanban

Storage

PostgreSQL, MongoDB

Platforms

Google Cloud Platform (GCP), Visual Studio Code (VS Code), Amazon Web Services (AWS), Azure IaaS, Linux, Windows, MacOS, Heroku, AlchemyAPI, iOS, Docker, Azure, Jupyter Notebook

Industry Expertise

Healthcare

Other

Natural Language Processing (NLP), Algorithms, SaaS, Computer Vision, Machine Learning, Artificial Intelligence (AI), Exploratory Data Analysis, APIs, Technical Hiring, Source Code Review, Code Review, Task Analysis, Interviewing, Generative Pre-trained Transformers (GPT), Language Models, Chatbots, Chatbot Conversation Design, Large Language Models (LLMs), Retrieval-augmented Generation (RAG), OpenAI, OpenAI GPT-4 API, OpenAI GPT-3 API, PaLM 2, Google Gecko Embeddings, Claude, LangChain, AI Research, Benchmarking, Datasets, Evaluation, Vector Stores, Vector Search, Prompt Engineering, MTEB, Large Model Systems Organization (LMSYS), Google Colaboratory (Colab), Generative Artificial Intelligence (GenAI), Generative AI, Generative Pre-trained Transformer 3 (GPT-3), Architecture, Artificial Neural Networks (ANN), Image Recognition, Sentiment Analysis, JSON REST APIs, SDKs, Deep Learning, Statistical Learning, Web Scraping, 3D Image Processing, Image Processing, Team Management, ChromaDB, Qdrant, Research, AI Agents, Full-stack Development, iPaaS, Laspy, PDAL, BizTalk Server, Outlook, Windows Communication Foundation (WCF), Systems, Engineering, Workflow, Profiling, Convolutional Neural Networks (CNN), Deep Neural Networks, Neural Networks, Data Structures, Recurrent Neural Networks (RNNs), Gated Recurrent Unit (GRU), Sequence Models, Hyperparameters, Regularization, Semantic Analysis, Rankings, Tf-idf, RSS Feeds, Discrete Mathematics, Graph Theory, Games, 2D Games, Mathematics, Game Art, LiDAR, Full-stack, IVR, Interactive Voice Response (IVR), Dialog Systems, Machine Learning Operations (MLOps), Labeling, Time Series Analysis, Reinforcement Learning, Time Series, Fintech, Cryptocurrency, Medical Imaging, Hybrid Search, Amazon Bedrock, Llama 2, GitHub Copilot Chat

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