Bradley Sliz is a Senior Machine Learning Engineer with a decade of experience building scalable computer vision and deep learning systems for cloud and edge deployments. He excels at productionizing models—authoring custom PyTorch services, vector search at 10M+ scale, and Triton/gRPC-based serving stacks—while keeping infrastructure cost and observability front of mind. Bradley pairs hands-on engineering (Python, Docker, TensorFlow/PyTorch, AWS) with product-focused architecture, having led teams, CI/CD culture, and standardized model-serving frameworks that reduce boilerplate across organizations. His background spans applied research to production robotics and IoT—founding a consultancy that powered commercial robotic deployments in casinos and factories—so he’s comfortable with low-latency, hardware-integrated pipelines as well as large-scale semantic search. Notably, he built an agentic fraud-detection pipeline marrying LLMs and custom tooling, showing a knack for blending NLP and CV to solve novel business problems. Based in Libertyville, IL, he brings both systems-level rigor and pragmatic delivery to cross-functional ML programs.
9 years of coding experience
11 years of employment as a software developer
Bachelor of Science, Engineering Physics -Computational Physics, Bachelor of Science, Engineering Physics -Computational Physics at Eastern Illinois University
University of Illinois Urbana-Champaign
Master of Science, Predictive Analytics, Master of Science, Predictive Analytics at Northwestern University
Contributions:39 commits, 19 pushes, 1 branch in 11 months
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Bradley Sliz - Senior Machine Learning Engineer at Collectors