Robert Crowe

San Jose, California, United States

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Summary

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Rockstar

🎓

Top School

Robert Crowe is an AI product leader and engineer with 7 years of experience turning ML research into production-grade ecosystems, most notably launching the JAX AI Stack and scaling TFX at Google. He blends technical product strategy, developer relations, and hands-on engineering—authoring the O’Reilly book "Machine Learning Production Systems" and creating the JAXup enablement program that became a prerequisite for Google AI Specialists. Robert has driven developer education at scale (Coursera specialization with 54k+ students, 23-video JAX series, 37+ conference keynotes, and millions of views) while also contributing to core open-source MLOps projects like TFX and workshop tooling. He’s skilled at removing strategic adoption blockers and packaging complex infrastructure into reproducible learning artifacts: decks, notebooks, API references, and production examples. Based in San Jose, he seeks high-autonomy roles focused on foundational frameworks, MLOps, or AI/ML infrastructure where he can move quickly from roadmap to global developer impact.

7 years of coding experience

16 years of employment as a software developer

Machine Learning, Machine Learning at Stanford Online / Coursera

Artificial Intelligence Nanodegree Artificial Intelligence, Artificial Intelligence Nanodegree Artificial Intelligence at Udacity

Big Data Series Machine Learning / Apache Spark, Big Data Series Machine Learning / Apache Spark at UC BerkeleyX / edX

University of California Santa Cruz

Stackoverflow

Stats

363reputation

33kreached

6answers

3questions

Github Skills (24)

notebook10

docker10

python10

tfx10

machine-learning10

dockers10

tensorflow10

scripting9

documentation9

shell9

script9

sh9

airflow8

gcp8

automation7

Programming languages (4)

C++ScalaJupyter NotebookPython

Github contributions (5)

tensorflow/workshops

Sep 2019 - Apr 2021

A few exercises for use at events.

Role in this project:

MLOps Engineer

Contributions:32 commits, 10 PRs, 90 pushes in 1 year 7 months

Contributions summary:Robert primarily focused on developing and configuring environments for a machine-learning workshop. Their contributions included setting up Docker images, creating directories, and configuring environment variables to run TFX components and Jupyter notebooks. They also modified shell scripts to manage the workshop container, pulling images, cloning TFX, and starting services. Further modifications involved moving to cloud environments such as GCloud, and integrating with cloud services.

javaevents

tensorflow/tfx

Mar 2019 - Oct 2022

TFX is an end-to-end platform for deploying production ML pipelines

Role in this project:

Full-stack Developer

Contributions:25 reviews, 168 commits, 7 PRs in 3 years 8 months

Contributions summary:Robert contributed to the TFX-OSS User Guide, updating and adding instructions for Chicago Taxi notebooks. The commits involve modifications to example notebooks, specifically adding and updating links to reference the README for running the notebooks. The changes also include the addition of a TensorFlow Model Analysis Colab example, indicating an effort to enhance the documentation and usability of the TFX framework for end-users.

deployingend-to-endml-pipelinesmlmlops

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