Jason Trost
Machine Learning Engineer at Databricks, Inc.
Atlanta, Georgia, United States
Summary
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RockstarJason Trost is a cybersecurity and data engineering leader with 14 years of experience building large-scale detection, analytics, and threat-hunting platforms across cloud and enterprise environments. Currently Head of Detection Engineering at Databricks, he designs production-grade Detection-as-Code frameworks and a network threat graph that materially improved cloud threat visibility and prioritized high-risk incidents. His background spans hands-on big-data systems at Capital One and HSBC to leading threat research and open-source projects like the widely used Modern Honey Network (MHN), reflecting deep expertise in Hadoop, Spark, Accumulo, and ELK. He blends strategic program leadership with technical delivery—driving cost reductions, scalable ingestion pipelines, and measurable detection coverage gains—while retaining a penchant for mentoring and team building. Jason’s work often sits at the intersection of ML, large-scale telemetry, and automation, and he has a track record of turning noisy threat intelligence into actionable, low-false-positive detections. Based in Atlanta, he pairs an MS in Information Security from Georgia Tech with a pragmatic, research-driven approach to defending cloud-native ecosystems.
14 years of coding experience
Github Skills (19)
administrator10
admin10
scripting10
linux10
bash10
supervisord10
script10
administration10
sup10
system-administration10
sh10
shell10
devops10
automation9
automations9
Programming languages (9)
Github contributions (5)
pwnlandia/mhn
May 2014 - Dec 2016
Modern Honey Network
Role in this project:
DevOps Engineer
DevOps EngineerContributions:384 commits, 84 PRs, 106 pushes in 2 years 8 months
Contributions summary:Jason primarily contributed to the setup and configuration of a Modern Honey Network (MHN) environment. They added installation scripts for components like the HPFeeds broker, Mnemosyne, and the MHN server itself. Their work included setting up Nginx, configuring supervisor for process management, and integrating with Elasticsearch (ELK stack), showcasing a focus on automation and infrastructure management.
golangblockchainhoney
jatrost/deep-learning
Mar 2017 - Jun 2017
Contributions:26 commits, 26 pushes, 5 branches in 3 months
pytorchdeep-learning-nanodegreenanodegreefoundationsdeep-learning
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