Amplify News
5.10.2021
Welcome Shreya Shankar

By Sarah Catanzaro and Mike Dauber

Every once in a while, you get lucky. In the Summer of 2018, Shreya Shankar applied to our University Associate internship program. We immediately knew she was someone special as she shared thoughtful insights on key trends around adversarial machine learning and probabilistic programming. Shreya also provided invaluable feedback on startups building developer tools, enterprise infrastructure, and ML platforms. We stayed close to Shreya as she completed her Masters at Stanford and watched with great anticipation as she joined Viaduct as their first ML Engineer.

In our regular catch-ups with Shreya, a few things (beyond being incredibly smart) stood out to us:

  • Deep understanding of the challenges in getting and maintaining ML models in production informed by expertise not only in machine learning but also in systems and data management
  • Incredibly authentic — she’s developed an impressive following in the ML community (she’s a must-follow on Twitter). She’s also consistently demonstrated a commitment to helping others build with ML
  • A burning desire to solve real problems that plague ML engineers

At Amplify, we talk a lot about practitioners turned founders — people who live through a problem and then are maniacal about solving it, first for themselves and then others. Some of our best companies came from pursuing this persona — Datadog, Fastly, dbt, Gremlin, and Hex, to name just a few. At Viaduct, Shreya experienced first-hand the challenge of iterating upon ML models and maintaining them in production. While there, she started to build tools that would help her work more efficiently and build more robust ML pipelines. As we spent more time with Shreya last year, it became clear that she had the passion to start a project and make these capabilities accessible to thousands of other ML engineers struggling with similar obstacles.

Today, we’re excited to announce that Shreya has joined Amplify as an EIR focused on building a tool for ML pipeline debugging. Shreya has a lot more to say about what she’s working on here. We can’t wait to see where this goes. Welcome, Shreya!

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