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Michael Wee

Strategy Lead at Eigen Labs

San Francisco Bay Area

Overview 

Michael Wee is a Strategy Lead at Eigen Labs, a Venture Partner at Portage, and has held roles such as Product Manager at Coinbase and Partner at Andreessen Horowitz. He has a diverse background with experience in software engineering, product management, and venture capital, having worked at notable companies like OpenGov Inc and Intuit. Wee has a strong educational background, having studied at UC Berkeley, Harvard Business School, and MIT, and has a wide range of skills including Java, SQL, Python, and machine learning. His career highlights include founding a startup and working as a Partner at a prominent venture capital firm.

Work Experience 

  • Strategy Lead

    2024 - Current

EigenLabs offers access to Ethereum's staked capital and validator set, supporting restaking, unstaking, and AVS management.

  • Venture Partner

    2024

  • Partner

    2022 - 2024

  • Product Manager

    2021 - 2022

    First member of the Coinbase Incubations team working closely with Brian Armstrong, Sanchan Saxena, and Surojit Chatterjee to originate new ideas (0 to 1) and grow emerging products (1 to n): • PM, Coinbase Commerce (1 to n) • Founding PM, Trust and Safety (0 to 1)

Coinbase Ventures is an investment arm of Coinbase that aims to invest in seed-stage cryptocurrency and blockchain startups.

  • Startup Founder

    2019 - 2021

    Built, launched, and iterated different product ideas in Enterprise and Consumer

  • Partner

    2016 - 2019

    Investments in enterprise infrastructure and applications, AI, web3, and emerging consumer platforms (augmented/virtual reality, self-driving cars), working closely with Marc Andreessen, Ben Horowitz, Chris Dixon, Martin Casado, and Peter Levine. Board Observer at Udacity, Mesosphere, DigitalOcean, Forward Networks, Instart Logic.

Andreessen Horowitz is a stage-agnostic venture capital firm with assets under management across multiple funds.

  • Full Stack Engineer and Data Scientist

    2014 - 2016

    • Worked on the data science team building out projections services, baseline methods, and model evaluation pipelines for Current Year month-over-month data. • Worked on the Data Platform, building smart data ingestion, processing, and storage platforms and tools for mapping, manipulating, and exploring customer data. Multidimensional input data includes Transactions Lines, General Ledgers and Charts of Accounts. Led the design and implementation of an initiative to unify our new Data Platform system with existing backend systems and front-end reporting tools. • Built a City Comparisons application, a tool that allows city managers to visually compare and analyze spending against a set of similar cities. Users can also overlay additional data sources such as census metrics as well as scale and manipulate the data to bring context to the comparison. • Worked with Ruby on Rails, Python, Spark, PostgreSQL. Experience with Javascript & React

OpenGov is a digital cloud software provider that helps local governments and state agencies run government operations.

Raised $178,000,000.00 from Alumni Ventures, Cox Enterprises, Alumni Ventures, Castor Ventures and Lauder Partners.

  • Research Assistant

    2013 - 2013

    Research in machine learning with Patrick Winston.

  • Software Engineering Intern

    2013 - 2013

    Built a trigger-based recommendation system for Intuit's QuickBooks Online and QuickBooks Desktop offerings to recommend add-on products such as Payments, Payroll, and third party offerings to customers for greater delight.

Intuit Turbo is an app to get financial reports and financial advice.

  • Research Assistant

    2013 - 2013

    Worked on StreetBump in collaboration with the City of Boston to classify street defects based on crowdsourced accelerometer data from smartphones in order to expedite maintenance of roads. Collected test data, conducted data exploration, and machine learning.

  • Research Assistant

    2011 - 2012

    Worked on Artificial Intelligence theory to improve on the state of the art of Computer Go. Worked with metareasoning, upper confidence bounding applied to trees, and implemented a Monte Carlo UCT Computer Go agent.

Articles About Michael

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