Hendrik Tillman

San Francisco Bay Area United States

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Summary

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Rockstar

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Top School

Hendrik Tillman is a machine learning and systems engineer with 11 years of hands-on experience building scalable search, ML, and infrastructure systems across product and research settings. A UC Berkeley EECS graduate with Highest Honors, he has interned at nine venture-backed startups and now develops cross-domain ranking and shared embedding spaces for Siri, Safari, and Spotlight at Apple. His background spans full-stack, low-latency C++ trading services, Go backends, React frontends, and Python-driven ML tooling, reflecting strong multidisciplinary fluency. He contributed to Ray’s autoscaler and GCP integration, highlighting practical expertise in cloud authentication, IAM, and deployment automation for a prominent open-source AI compute engine. Past research at Berkeley RISE Lab produced novel explainability techniques for image segmentation, showing a bridge between foundational research and production systems. Based in the San Francisco Bay Area, he combines fast iteration at startups with rigorous engineering practices used in large-scale consumer products.

11 years of coding experience

7 years of employment as a software developer

Computer Science, Computer Science at UC Berkeley Extension

Computer Science, Computer Science at College of Marin

Computer Science, Computer Science at Harvard University Extension

Bachelor of Science - BS With Highest Honors, Electrical Engineering and Computer Sciences (EECS), Bachelor of Science - BS With Highest Honors, Electrical Engineering and Computer Sciences (EECS) at UC Berkeley College of Engineering

Computer Science, Computer Science at City College of San Francisco

National Taiwan University, University of California Education Abroad Program

Computer Science, Computer Science at Cloudera University

English, Chinese

Stackoverflow

Stats

11reputation

10kreached

1answer

0questions

Github Skills (13)

autoscaling10

cloud-infrastructure10

deploying10

devops10

python10

gcp10

javascript6

jquery6

kubernetes4

terraformer4

terraform4

kubernetes-pods4

machine-learning3

Programming languages (3)

JavaScriptGoPython

Github contributions (5)

ray-project/ray

Jun 2020 - Aug 2020

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Role in this project:

DevOps Engineer & Cloud Engineer

Contributions:6 commits, 6 PRs, 5 comments in 1 month

Contributions summary:Hendrik contributed to Ray's autoscaler functionality, focusing on infrastructure and cloud-related tasks. Their work includes implementing GCP authentication using OAuth tokens, configuring IAM roles, and setting up SSH key pairs. They also addressed configuration issues related to GCP, including creating a directory for ssh keys. Furthermore, the user removed fingerprint checks, suggesting work on improving deployment or network configuration.

pythonconsistsruntimetensorflowserving

henktillman/106b_lab1

Feb 2018 - Feb 2018

Contributions:10 commits, 9 pushes, 1 branch in 6 days

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