Marcus Way
Verified Expert in Engineering
Distributed Systems Developer
Weare, NH, United States
Toptal 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.
Portfolio
Experience
- Python - 10 years
- Amazon Web Services (AWS) - 8 years
- REST - 7 years
- Distributed Systems - 7 years
- Java - 7 years
- Machine Learning - 6 years
- Swift - 4 years
- PostgreSQL - 3 years
Availability
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.
Work Experience
Co-founder
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.
Senior Engineer, Technical Lead
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.
Software Development Engineer
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.
Full-stack Engineer
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.
Research Assistant
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.
Experience
Blueprint iOS App
http://blueprintapp.coI 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.
Education
Bachelor's Degree in Neurobiology and Economics
Harvard University - Cambridge, MA
Skills
Libraries/APIs
Node.js, Apple Subscriptions
Tools
Amazon Simple Queue Service (SQS), Git, MATLAB, Terraform, Amazon Elastic Container Service (ECS), AWS Fargate, Hygraph (GraphCMS)
Languages
Python, SQL, Java, Swift, JavaScript, GraphQL
Storage
PostgreSQL, Cassandra, Datadog, Amazon DynamoDB, MongoDB, Neo4j
Frameworks
Flask
Paradigms
REST, Continuous Delivery (CD)
Platforms
Amazon Web Services (AWS), Docker, Linux, Apache Kafka, Kubernetes, iOS
Other
Distributed Systems, Scaling, Machine Learning, APIs, CI/CD Pipelines, Science, Natural Language Processing (NLP), Web Scraping, EEG, fMRI, FastAPI, Generative Pre-trained Transformers (GPT)
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