Old Bear
Marketing Specialist at Nemesis Media LLC
Provo, Utah, United States
Summary
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RockstarOld Bear is a Marketing Specialist based in Provo, Utah with 11 years of experience blending technical contribution and product-minded communication. Although his current role centers on marketing at Nemesis Media LLC, he has a substantive software engineering background demonstrated by open-source contributions to high-profile projects like Ray and Apache brpc. His work on Ray added AutoML capabilities via a GeneticSearcher and improved trial reporting, showing comfort with machine learning tooling and algorithm design. In brpc he strengthened testing and SSL-related build robustness, reflecting attention to reliability and systems-level detail. This mix of marketing and hands-on engineering enables him to translate complex technical concepts into compelling narratives and practical improvements. Colleagues value his rare combination of cross-disciplinary fluency and a focus on shipping resilient solutions.
11 years of coding experience
Github Skills (18)
c-language10
ssl10
python10
testing10
machine-learning10
hyperparameter-optimization10
ray10
cprogramming-language10
data-science9
unit-testing9
openssl9
deeplearning-ai9
rpc9
deep-learning9
distribute8
Programming languages (4)
Github contributions (5)
apache/brpc
Sep 2017 - Jan 2019
brpc is an Industrial-grade RPC framework using C++ Language, which is often used in high performance system such as Search, Storage, Machine learning, Advertisement, Recommendation etc. "brpc" means "better RPC".
Role in this project:
Back-end Developer / Test Automation Engineer
Back-end Developer / Test Automation EngineerContributions:2 reviews, 26 commits, 11 PRs in 1 year 4 months
Contributions summary:Old primarily contributed to improving the testing infrastructure and reliability of the brpc framework. Their work focused on enhancing unit tests, specifically addressing issues related to dependencies on external tools like `curl` and implementing SNI testing with `openssl`. Furthermore, they addressed build issues by removing a non-existent include file and added SSL-related configurations. These changes suggest a strong emphasis on ensuring the robustness and correctness of brpc's core functionality.
cppmachine-learningrpc
ray-project/ray
Aug 2018 - Oct 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:ML Engineer
ML EngineerContributions:5 commits, 7 PRs, 56 comments in 1 month
Contributions summary:Old contributed to the Ray project by addressing compatibility issues related to Python 2 and string handling within the `ray.tune` module. They implemented support for infinity values in the `report result` function, enhancing the trial reporting capabilities. Furthermore, the user developed and integrated a new AutoML algorithm, the GeneticSearcher, introducing key components such as the searcher framework and mechanisms for selection, crossover, and mutation within the AutoML pipeline.
aimachine-learningraydistributedparallel
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