Marcus Way, Distributed Systems Developer in Weare, NH, United States
Marcus Way

Distributed Systems Developer in Weare, NH, United States

Member since April 7, 2022
Marcus has spent over a decade in software and machine learning (ML). He's developed ML models for a neuroscience lab, was an engineer at a consumer travel startup and worked on Amazon Alexa's ML data platform. Marcus led a software and data infrastructure team at WHOOP (a fitness wearable company) as they grew exponentially (from a $125 million to $3.6 billion valuation) over two and a half years. He's also a co-founder and sole technical contributor to a highly rated iOS app.
Marcus is now available for hire

Portfolio

  • Blueprint
    Amazon Web Services (AWS), Terraform, Python, FastAPI, PostgreSQL, Swift, iOS...
  • WHOOP
    Node.js, PostgreSQL, Amazon Simple Queue Service (SQS)...
  • Amazon
    Amazon Web Services (AWS), Amazon DynamoDB, Amazon Simple Queue Service (SQS)...

Experience

Location

Weare, NH, United States

Availability

Part-time

Preferred Environment

MacOS, Distributed Systems, PostgreSQL, Cassandra, Apache Kafka, Amazon Web Services (AWS), Python, Java, Swift, Machine Learning

The most amazing...

...experience I’ve had was leading a physiological data processing team at WHOOP as we grew to become the most valuable standalone wearable companies globally.

Employment

  • Co-founder

    2019 - PRESENT
    Blueprint
    • Designed and implemented all technical aspects of the product, Blueprint, an iOS app for helping people understand themselves and others through the Enneagram personality model.
    • Developed a mobile app in Swift, with the back end in Python and FastAPI backed by PostgresSQL and AWS RDS, running on AWS ECS and AWS Fargate.
    • Created analytics dashboards to measure product engagement and subscription data to drive product decisions.
    • Prioritized full-stack observability using Datadog, RUM, and error tracking.
    • Set up front and back-end CI/CD using Terraform, GitHub Actions, and Visual Studio App Center.
    Technologies: Amazon Web Services (AWS), Terraform, Python, FastAPI, PostgreSQL, Swift, iOS, Apple Subscriptions
  • Senior Engineer, Technical Lead

    2019 - 2021
    WHOOP
    • Chartered and led a team responsible for scaling core physiological data processing during massive company growth.
    • Collaborated directly with infrastructure, data science, software, and product teams to support new product features and evolve ML algorithms for better accuracy and efficiency, including increasing sleep processing throughput by 40 times.
    • Became an expert in the physiological data processing pipeline, providing documentation and visibility into mysterious legacy systems, ultimately evolving the architecture, eliminating legacy code, and reducing operational incidents by 20 times.
    • Took ownership of Python development practices, introducing tooling and standard procedures in automated testing, instrumentation, structured logging, and exception reporting.
    • Oversaw hiring and performance reviews, expanding the team from two to seven engineers.
    • Advocated for creating a dedicated ML operations team and developed the roadmap with buy-in from the VPs of engineering and data science.
    • Designed and implemented the back end for a behavior tracking feature, which allows users to gain insights on the impact of their behaviors on sleep and recovery metrics. Tracked hundreds of millions of data points.
    Technologies: Node.js, PostgreSQL, Amazon Simple Queue Service (SQS), Amazon Web Services (AWS), Apache Kafka, Kubernetes, REST, Distributed Systems, Python, Java, Cassandra, Datadog
  • Software Development Engineer

    2015 - 2019
    Amazon
    • Worked on a platform that facilitates manual data labeling for ML dataset creation. Generated thousands of platform users and millions of labels each week for hundreds of ML use cases across Amazon.
    • Designed and implemented an experiment to identify redundant manual transcription effort, which led to a process change that decreased cost per transcription by 44%.
    • Worked closely with speech scientists to develop an active learning framework as part of the platform.
    • Published and presented an internal paper about the platform and the active learning methodologies at the annual ML conference.
    • Led service regionalization efforts required for GDPR compliance.
    Technologies: Amazon Web Services (AWS), Amazon DynamoDB, Amazon Simple Queue Service (SQS), Python, Java, Machine Learning, Natural Language Processing (NLP), Distributed Systems
  • Full-stack Engineer

    2013 - 2015
    Wanderu
    • Used Python, MongoDB, and Neo4j to scrape, parse, and store bus ticket data and make automated purchases through partner company sites.
    • Co-led development of an iOS app, which has been featured in the Apple App Store as one of the “Best New Apps” and “Best Travel Apps of 2015”.
    • Conceived, designed, and implemented a system to infer bus schedules and make ticket price predictions from existing ticket data.
    Technologies: Python, Web Scraping, MongoDB, Neo4j, Node.js, Swift, iOS
  • Research Assistant

    2012 - 2014
    Boston Children's Hospital
    • Applied novel signal processing and ML techniques to neuroimaging (EEG and fMRI) data.
    • Co-authored multiple publications on developmental neuroscience.
    • Automated much of the lab's EEG analysis process with MATLAB, Python, and Bash.
    Technologies: Python, Machine Learning, MATLAB, EEG, fMRI

Experience

  • Blueprint iOS App
    http://blueprintapp.co

    Blueprint is an iOS app for helping people understand themselves and others through the Enneagram personality model. It has been live on the App Store since February 2022 and has a 4.98-star rating as of April 2.

    I was the sole technical member of a team of four working on the app. I wrote all the mobile and back-end code and set up and managed the back-end infrastructure to support the app. I worked with our copywriters to define content models and a process for content creation and publication. I also created analytics dashboards to measure product engagement and subscription data.

Skills

  • Languages

    Python, SQL, Java, Swift, JavaScript, GraphQL
  • Storage

    PostgreSQL, Cassandra, Datadog, Amazon DynamoDB, MongoDB, Neo4j
  • Other

    Distributed Systems, Scaling, Machine Learning, APIs, CI/CD Pipelines, Science, Natural Language Processing (NLP), Web Scraping, EEG, fMRI, FastAPI
  • Frameworks

    Flask
  • Tools

    Amazon Simple Queue Service (SQS), Git, MATLAB, Terraform, Amazon Elastic Container Service (Amazon ECS), AWS Fargate, GraphCMS
  • Paradigms

    REST, Continuous Delivery (CD)
  • Platforms

    Amazon Web Services (AWS), Docker, Linux, Apache Kafka, Kubernetes, iOS
  • Libraries/APIs

    Node.js, Apple Subscriptions

Education

  • Bachelor's Degree in Neurobiology and Economics
    2008 - 2012
    Harvard University - Cambridge, MA

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