Apoorv Khandelwal, Software Developer in San Francisco, CA, United States
Apoorv Khandelwal

Software Developer in San Francisco, CA, United States

Member since November 11, 2021
Apoorv is a dataholic who loves to use machine learning to discover novel insights from complex data. He draws experience from his stints at tech giants such as Carnegie Mellon, Amazon, and LinkedIn. His own startup was selected for the Techstars accelerator class of 2019. His software engineering, machine learning, and data analysis contributions have led to multiple patents and a $100 million company acquisition in the past. Apoorv is most passionate about projects in education technology.
Apoorv is now available for hire


  • ADEx
    Elasticsearch, Spring, Play, Neo4j, MongoDB, Jira, AWS...
  • LinkedIn
    Java, Machine Learning, Apache Pig, Spark, Scala, Deep Learning...
  • Connectifier
    Java, Play, Angular, Scala, Machine Learning, Factorization Machines, MongoDB



San Francisco, CA, United States



Preferred Environment

Spring, Java, Python, Probability Theory, Data Analysis, Machine Learning, Google Cloud Platform (GCP), Data Visualization

The most amazing...

...engine I built determined where a country should allocate its GDP budget in the future, to maximize the number of UN Sustainable Development Goals it achieves.


  • CTO and Co-founder

    2018 - PRESENT
    • Selected for the 2019 class of Colliers Proptech Accelerator powered by Techstars.
    • Built and led a team of up to ten engineers to build an AI platform for automatically summarizing and reviewing users' documents.
    • Developed technology partnerships with companies like Box and Salesforce.
    • Obtained and maintained giant enterprise clients in the real estate space.
    Technologies: Elasticsearch, Spring, Play, Neo4j, MongoDB, Jira, AWS, Google Cloud Platform (GCP), Docker, Flask, Python, Deep Learning, Angular
  • Senior Software Engineer

    2016 - 2018
    • Taught learning-to-rank methodology to other engineers, as one of LinkedIn's AI Academy's inaugural teachers.
    • Drove the targeting of two-way interest for search results (i.e. candidates accepting inmails), instead of just recruiter engagement (i.e. recruiters sending inmails). This caused fewer complaints from users bombarded by irrelevant inmails.
    • Patented several techniques including document parsing, factorization machines, and impression discounting.
    • Migrated our team's offline training dataset generation pipeline from Pig to Spark, to allow for easier testing, debugging, and maintainability.
    • Created a model which incorporated impression discounting features for the Recruiter Search product. This caused more inmail accepts and a healthier overall Recruiter Search ecosystem.
    Technologies: Java, Machine Learning, Apache Pig, Spark, Scala, Deep Learning, Data Analysis, Search
  • Software Engineer

    2015 - 2016
    • Was integral in its team of ten developers, allowing the company to be acqui-hired by LinkedIn for over $100 million.
    • Improved Connectifier's company canonicalization as well as retrieval of data from crawled resumes.
    • Added to the company's AutoSearch extension a way to show Connectifier search results, even upon a user's searches on other sites.
    Technologies: Java, Play, Angular, Scala, Machine Learning, Factorization Machines, MongoDB
  • Software Development Engineer II

    2013 - 2015
    • Rolled out machine learning models that improved Amazon's forecasts of demand for products under promotions, for all world regions.
    • Integrated IPyNotebook running on PySpark with our platform so that software developers, research scientists, and data analysts could access, transform, and share data effectively.
    • Designed and deployed software that allowed downstream clients to bias-correct our team's forecasts in bulk.
    Technologies: Java, Hadoop, Spark, IPython Notebook, AWS, Random Forests, Machine Learning, Software Engineering, Apache Hive


  • ADEx, Inc.

    I am the CTO and co-founder of this company founded in 2018. It is a cloud-based collaborative website that uses AI to automatically uncover relevant data points from users' corporate documents. Users then review these in our intuitive and interactive environment. Finally, they can export the structured data to downstream systems.

    ADEx's clients are large enterprises that have a large volume of existing or yearly contracts. One Australian client wanted to know whether it should invest in a new property in the city. We were able to bring online many existing leases in the city, allowing the client to access the necessary comparables and clauses. Using our product allowed this client to decide to pursue the property investment and define appropriate terms for its contract.

    As the CTO and co-founder, I have so far scaled up the company to an ARR of a million dollars and a team of 15 employees. ADEx has helped about a dozen large companies by reducing their manual contract review time by a factor of four. Along with this speedup, clients have experienced more accurate standardization of their data and reduced overall cost.

  • Effective EdTech, LLC

    Effective EdTech develops various effective education and design solutions, ranging from training programs to infographics to presentations.

    I co-founded the company, managed client relationships, and supervised the consultants to deliver successful projects. Our clients are small and medium-sized businesses.

    One client company had a technical software product offering sophisticated reports, which its customers had difficulty learning. So Effective EdTech developed off-line documentation, real-time tutorials, and even a game-like quiz for the software. With these onboarding steps, the client's customers' average time-to-first-report decreased from four hours to just one hour. The client's number of customer support requests from new users became virtually nil as an additional benefit.

    Another client had a fledgling company that he was trying to crowdfund. He needed to persuade potential investors why his luxury brand would become viral. We compiled data from tens of market and scientific studies, and it created infographics and a presentation that intuitively visualized the supporting data. This client was thus able to raise tens of thousands of dollars and jump-start his business.


  • Languages

    Java, Python, Python 3, Scala, R
  • Frameworks

    Spring, Play, Flask, Hadoop, Spark, Angular
  • Tools

    IntelliJ, Jira, Postman, MATLAB, IPython Notebook, Mathematica, Adobe Creative Suite, Canva, Prezi, Articulate Storyline
  • Platforms

    Google Cloud Platform (GCP), Apache Pig, Docker
  • Storage

    MongoDB, Elasticsearch, Neo4j, Apache Hive
  • Other

    Web App Development, Machine Learning, Probability Theory, Random Forests, Software Engineering, Data Analysis, Data Visualization, Discrete Mathematics, Natural Language Processing (NLP), AWS, Digital Signal Processing, Signal Processing, Statistics, Algorithms, Physics, Deep Learning, Search, Factorization Machines


  • Master of Science in Electrical and Computer Engineering
    2012 - 2013
    Carnegie Mellon University - Pittsburgh, PA
  • Bachelor of Science in Electrical and Computer Engineering
    2008 - 2012
    Carnegie Mellon University - Pittsburgh, PA

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