Jim Rohrer
Senior MLOps Engineer at Gaggle
North Sioux City, South Dakota, United States
Summary
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Rockstar🎓
Top SchoolJim Rohrer is a Senior MLOps Engineer with over a decade of hands-on experience building reliable, automated cloud systems and production ML pipelines. He blends full-stack and DevOps expertise—particularly in AWS (ECS, SageMaker, Lambda, CloudFormation) and infrastructure-as-code—with a track record of reducing deployment friction through CI/CD and automation. At Gaggle he leads ML architecture decisions to serve real-time NLP and computer vision models while partnering with data scientists to automate end-to-end training, deployment, and monitoring. His background includes deep DevOps consulting at Stelligent and contributions to the popular stelligent/mu project, where he improved CI/CD reliability around S3-backed repositories and git revisioning. Based in North Sioux City, he’s known for designing repeatable, testable systems that let engineers focus on code rather than deployment.
11 years of coding experience
18 years of employment as a software developer
Wright State University
English
Stackoverflow
1reputation
402reached
1answer
1question
Github Skills (16)
aws-s310
go10
aws10
amazon-s310
devops10
aws-codepipeline10
pipe10
cicd10
s3-bucket10
pipeline10
yaml9
githubaction-workflow9
github-ci9
django-rest-framework6
python6
Programming languages (9)
Github contributions (5)
stelligent/mu
Oct 2017 - Aug 2019
A full-stack DevOps on AWS framework
Role in this project:
DevOps Engineer
DevOps EngineerContributions:18 commits, 11 PRs, 7 pushes in 1 year 10 months
Contributions summary:Jim primarily contributed to the configuration and maintenance of the CI/CD pipeline within the "mu" framework. Their work involved modifying the `mu.yml` configuration and adjusting the Go code to properly handle source code repositories, specifically focusing on S3 buckets and object keys. Additionally, they implemented fixes to ensure accurate git revision identification and versioning within the pipeline, improving the reliability of automated builds and deployments.
cloud-infrastructuredevopsfull-stackserverlessaws-lambda
akuma12/sagemaker-python-sdk
Sep 2023 - Aug 2024
A library for training and deploying machine learning models on Amazon SageMaker
Contributions:40 pushes, 3 branches in 10 months
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