Benjamin Black
Senior Software Engineer at Techcyte
Idaho Falls, Idaho, United States
Summary
🤩
Rockstar🎓
Top SchoolBenjamin Black is a Senior Software Engineer with 11 years’ experience building end-to-end ML and systems solutions that move research into production. Based in Idaho Falls, he combines deep hands-on work—developing YOLO-based 3D FISH detection, high-throughput AWS inference pipelines, and a Rust library for large-scale box algorithms—with a knack for experimental design, data labeling, and reproducible ML experimentation. An active open-source contributor, he helped shape the PettingZoo multi-agent RL API and integrated its environments into Ray, reflecting his strength at bridging research-grade environments and production runtimes. He excels at reducing operational cost and complexity in regulated settings while keeping outputs bit-for-bit identical, and often surfaces subtle data-quality and testing issues others miss.
11 years of coding experience
4 years of employment as a software developer
Master's degree, Computer Science, Master's degree, Computer Science at University of MarylandBachelor’s Degree, Mathematics and Computer Science, Junior, Bachelor’s Degree, Mathematics and Computer Science, Junior at Reed College
English
Stackoverflow
461reputation
278kreached
8answers
0questions
Github Skills (18)
python10
machine-learning10
reinforcement-learning10
ray10
deeplearning-ai9
deep-learning9
aec9
data-science8
pytorch7
tensorflow7
visual-studio6
compiler-construction6
matrix6
x866
assembly6
Programming languages (7)
Github contributions (5)
Farama-Foundation/PettingZoo
Mar 2020 - Apr 2022
An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
Role in this project:
Backend Developer & DevOps Engineer
Backend Developer & DevOps EngineerContributions:15 releases, 123 reviews, 1071 commits in 2 years 1 month
Contributions summary:Benjamin's contributions centered around enhancing the `pettingzoo` repository. Their work included the implementation of a `NanZerosWrapper` and integration of the `sisl` library to utilize this wrapper, which involved code modifications in `pettingzoo/utils/wrappers.py`, `pettingzoo/sisl/multiwalker/multiwalker.py`, and `pettingzoo/sisl/waterworld/waterworld.py`. In addition, they merged branches and integrated the `Hanabi` environment, suggesting a focus on environment integration and possibly testing. They also removed error codes from MPE and contributed to ale games' code.
agentreinforcement-learningreinforcement-learning-agentgymnasiumdeep-reinforcement-learning
ray-project/ray
Jul 2020 - Jan 2022
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:ML Engineer
ML EngineerContributions:3 reviews, 6 commits, 6 PRs in 1 year 6 months
Contributions summary:Benjamin's commits primarily focus on integrating and supporting the PettingZoo environment within the Ray project, an AI compute engine. They added, fixed, and updated the `PettingZooEnv` wrapper and related examples, including various fixes and API adaptations to incorporate the environment's functionality. This involved modifying the code for interaction with the `PettingZoo` environments, including support for different game versions and addressing linting and testing issues.
pythonconsistsruntimetensorflowserving
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