Peter Veerman
Software Engineer at Citadel Securities
Arcadia, California, United States
Summary
👤
Senior🎓
Top SchoolPeter Veerman is a software engineer with a decade of hands-on experience building distributed systems and production services, currently at Citadel Securities. He brings deep backend expertise—contributing to Ray’s distributed DataFrame functionality with Pandas-like APIs—and practical DevOps experience improving Kubernetes PVC provisioning for JupyterHub. His Berkeley CS background and RISE Lab work reflect a strong focus on scalable data tooling and performance (e.g., accelerating Pandas via Ray). Comfortable across finance and infrastructure domains, he has shipped NLP search tooling, cloud-hosted Jupyter tooling, and robust backend fixes in high-stakes environments. Known for pragmatic problem-solving, he pairs careful testing and debugging with contributions to high-profile open-source projects.
10 years of coding experience
1 year of employment as a software developer
Bachelor of Arts - BA Computer Science, Bachelor of Arts - BA Computer Science at University of California, Berkeley
English, Spanish
Github Skills (25)
kubernetes10
docker10
jupyterhub10
pytest10
python10
testing10
dataframes10
pandas10
dockers10
dataframe10
helm10
kubernetes-pods10
ray10
jupyter9
cloud-infrastructure9
Programming languages (5)
Github contributions (5)
ray-project/ray
Mar 2018 - May 2018
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:
Back-end Developer
Back-end DeveloperContributions:6 commits, 9 PRs, 10 comments in 2 months
Contributions summary:Peter primarily contributed to the implementation of Ray DataFrame functionalities, focusing on methods similar to Pandas. Their work included implementing `.fillna()`, `.ffill()`, `.bfill()`, `.eval()`, and `.drop()`, and `.pipe()` and `.as_matrix()` methods. They also added tests for these functionalities and fixed related issues. Additionally, the user contributed to implementing `rename`, `rename_axis` and `Index.set_names` within the Ray DataFrame library.
pythonconsistsruntimetensorflowserving
jupyterhub/kubespawner
Nov 2016 - Nov 2016
Kubernetes spawner for JupyterHub
Role in this project:DevOps Engineer
DevOps EngineerContributions:18 commits, 1 PR, 1 comment in 4 days
Contributions summary:Peter primarily focused on modifying the `kubespawner` project to dynamically provision PersistentVolumeClaims (PVCs) within a Kubernetes environment. They implemented code to handle PVC creation, ensuring that PVCs are created and managed correctly. The user also made changes to improve the PVC lifecycle and integrated debugging prints for monitoring.
spawnerjupyterhub-kubernetes-spawnerjupyterkuberneteskubernetes-cluster
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