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Abhimanyu Veer Aditya, Machine Learning Developer in San Francisco, CA, United States
Abhimanyu Veer Aditya

Machine Learning Developer in San Francisco, CA, United States

Member since May 7, 2019
Abhimanyu is a machine learning expert with 15 years of experience creating predictive solutions for business and scientific applications. He’s a cross-functional technology leader, experienced in building teams and working with C-level executives. Abhimanyu has a proven technical background in computer science and software engineering with expertise in high-performance computing, big data, algorithms, databases, and distributed systems.
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Portfolio

Experience

  • Machine Learning 15 years
  • High-tech Startups 10 years
  • Python 9 years
  • System Architecture 6 years
  • Optimization 6 years
  • Recommendation Systems 5 years
  • Natural Language Processing (NLP) 4 years
  • Time Series Analysis 3 years

Location

San Francisco, CA, United States

Availability

Part-time

Preferred Environment

Git, RHEL, CentOS, Ubuntu, Linux

The most amazing...

...experience I've had is starting and growing my own startup out of a lab at Georgia Tech to 70 full time employees and $30+ million in funding in Silicon Valley.

Employment

  • Self Employed

    2018 - PRESENT
    Independent Machine Learning Consultant
    • Built and deployed multiple personalization ML pipelines to lift offer/coupon conversion rate for customers of major restaurant chain. Application built on Azure Databricks platform with business-configurable pipelines for training, tuning, testing and prediction, using Pandas (Python), Spark (PySpark), sklearn and Spark ML. Deployment to production using Azure Data Factory.
    • Automated, hardened, and deployed multiple ML pipelines on AWS (Elastic Map Reduce with Spark and Lambda) to predict next-best-action, forecast performance and predict/prevent churn for sales representatives of major corporation. Data processing used Python, PySpark and Spark SQL. ML models built using Microsoft ML for Spark.
    • Advised a mid-stage startup on the requirements, features, and architecture needed to support ML pipelines in their high-speed stream processing framework and in-memory data grid. Worked directly with the CEO/CTO and senior technical team.
    Technologies: Optimization, Amazon S3 (AWS S3), Amazon EC2, Docker, Python, Pandas, Scikit-learn, XGBoost, Solution Architecture, System Architecture

  • Senior Product Architect, Infosys Nia (Palo Alto)

    2017 - 2018
    Infosys Technologies
    • Developed and prioritized the roadmap for the integration of Skytree software into Infosys Nia.
    • Trained 100+ Infosys sales leaders, solutions architects and data scientists on Skytree capabilities, technology, architecture, system requirements, demos etc. Also trained enterprise-wide data science teams on ML science and best practices.
    • Evangelized the newly acquired ML capabilities to Fortune 500 prospects as well as existing clients.
    Technologies: Amazon EC2, AWS EMR, Amazon S3 (AWS S3), HDFS, MapReduce, YARN, Hadoop, Scikit-learn, Pandas, NumPy, SciPy, Python, R, Linux, Bash, Java, OpenMP, MPI, C++, Machine Learning

  • Co-Founder

    2009 - 2017
    Skytree Inc.
    • Worked directly with our Fortune 500 customers and collaboratively built predictive machine learning models/pipelines for fraud detection (for American Express), product and media recommender systems (for Samsung), credit risk scoring - consumer and SMB (for American Express and Equifax), Lead Scoring - Premium Consumer Credit Card (for American Express), Balance Transfer Offer Optimization (for Discover), churn prevention (E-Harmony, ShoeDazzle), real estate price prediction (Brookfield RPS), and many others for Fortune 500 clients.
    • Led engineering and data science and ultimately moved to technical product management and ownership for Skytree’s flagship product. Led the research and development of Skytree’s high performance and massively parallel C++ library for tera-scale ML. Implemented (from scratch) mathematically scalable and distributed algorithms for nearest neighbors, random forests, gradient boosted trees, support vector machines, clustering, collaborative filtering, etc. for classification, regression, anomaly detection, and recommender systems. This included many first of the kind innovations in the practical application of ML algorithms to big data.
    • Architected Skytree’s (flagship) Infinity AI platform, including APIs, GUI, and SDKs. The Java-based server coordinated with the underlying multi-tenant Big Data or cloud infrastructure, managing data, users, resources, and scheduling jobs (a mix of Apache Spark for data processing and Skytree’s C++ engine for ML). Platform support included Apache Hadoop (YARN & HDFS) from MapR, Hortonworks, and Cloudera as well as AWS Elastic Map Reduce.
    • Delivered multiple releases of the full stack of Skytree’s AI software as the product manager for all four technical teams (ML, systems, UI, and data science), including defining and prioritizing the roadmap and coordinating release and development efforts across teams.
    • Built world-class engineering (C++/HPC/ML, Java/Systems, and UI) and data science team. Defined requirements, developed and reviewed screening tests, and finalized candidates.
    • Spearheaded the technical sales enablement efforts.
    • Supported POCs, pre and post-sales activities, renewals, through product demos, sales calls, requirements gathering, trade shows, webinars, seminars, and tutorials.
    • Trained solutions architects/sales engineers and had ownership of the technical resources they needed (demos, documentation, guides, questionnaires, etc.).
    • Co-authored five patent applications in the areas of ML user experience, recommender systems, and automatic feature engineering.
    • Recruited candidates for various other positions, from sales directors to senior leadership (VP of sales, marketing, and engineering).
    Technologies: Linux, Bash, Java, R, Pandas, NumPy, SciPy, Scikit-learn, Python, Amazon EC2, AWS EMR, Amazon S3 (AWS S3), HDFS, MapReduce, YARN, Hadoop, Apache Spark, OpenMP, MPI, C++

  • Graduate Research Assistant

    2007 - 2009
    Georgia Institute of Technology
    • Worked on integrating algorithmically optimized machine learning algorithms directly into SQL Server using the .NET platform and C# so that they ran natively inside the database under the purview of the database scheduler.
    • Designed innovative disk-based algorithms to piggyback multi-dimensional space trees over database indexes (B-Tree's) to minimize disk hit rate and optimize cash hit ratio.
    • Specialized in computational science and engineering, high-performance computing, and artificial intelligence.
    Technologies: .NET, Microsoft, Microsoft SQL Server, Java, C#

  • Software Developer (Intern), Analysis Services, SQL Server Team

    2008 - 2008
    Microsoft
    • Integrated advanced ML algorithms, optimized for disk-based I/O, as first-class objects into SQL Server Analysis Services and exposed these through the query interface- thus enabling ML models to run in-database.
    Technologies: C#, Microsoft SQL Server

  • Technical Associate

    2005 - 2007
    Trilogy
    • Designed and developed the software for Trilogy's email marketing service for, used by clients such as Gateway and Orbitz. The software used segmentation and association rule mining to increase sales, margins, and engagement (email opens and clicks), and integrated data such as demographic, email activity, clickstream, promotional, etc.
    • Executed weekly campaigns that generated millions of targeted emails, measured lift through A/B testing and reported results in the form of pivot tables and dashboards.
    Technologies: Microsoft SQL Server, Subversion (SVN), Microsoft, Java

Experience

  • Foresight, Inc.

    Foresight is an online service that makes automated machine learning easy to use, intuitive, and visual. It has powerful features built into it that slashes the amount of time from problem to data to predictive solution with readily available visualizations and an eye towards interpretable models and visual insights.

Skills

  • Languages

    JavaScript, Python, Java, C++, Bash, SQL, C#, R

  • Libraries/APIs

    XGBoost, MPI, Pandas, Flask-RESTful, Open MPI, OpenMP, REST APIs, Scikit-learn, SciPy, NumPy, Amazon EC2 API, SQLAlchemy, Matplotlib, Ggplot2

  • Tools

    H2O AutoML, Git, Plotly, GNU Dev Tools, Subversion (SVN), GCC, Amazon EBS, Amazon Elastic MapReduce (EMR), Boto 3

  • Paradigms

    Distributed Computing, Data Science, Parallel Computing, REST, Agile, MapReduce

  • Platforms

    Android, Linux RHEL/CentOS, Amazon EC2, Ubuntu, Amazon Web Services (AWS), Linux, CentOS, Microsoft, Docker, Eclipse

  • Other

    Machine Learning, Classification, Regression, Recommendation Systems, Artificial Intelligence (AI), Predictive Analytics, Supervised Learning, RHEL, Classification Algorithms, Regression Modeling, Algorithms, Predictive Modeling, Random Forests, Random Forest Regression, Gradient Boosted Trees, Decision Trees, Decision Tree Classification, Decision Tree Regression, Logistic Regression, Linear Regression, Software Development, Startups, Solution Architecture, Natural Language Processing (NLP), GNU, Optimization, Clustering Algorithms, High Code Quality, Time Series Analysis, Optimization Algorithms, High-tech Startups, Early-stage Startups, Entrepreneurship, System Architecture, Solution Design, Technical Product Management, A/B Testing, Agile Sprints, Neural Networks

  • Frameworks

    Apache Spark, Flask, .NET, AWS EMR, Hadoop, YARN

  • Storage

    MySQL, Microsoft SQL Server, Amazon S3 (AWS S3), HDFS

Education

  • Master of Science Degree in Computer Science
    2007 - 2009
    Georgia Institute of Technology - Atlanta, Georgia, USA
  • Bachelor of Technology Degree in Computer Science and Engineering
    2001 - 2005
    Manipal Institute of Technology - India

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