Sergey Togulev
Senior Software Engineer at EasyPost
Atlanta Metropolitan Area United States
Summary
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Rockstar🎓
Top SchoolSergey Togulev is a Senior Software Engineer with 8 years of experience building ML platforms, computer vision infrastructure, and GenAI systems across AdTech, fintech, and edtech, including a formative tenure at AWS working on SageMaker-related infrastructure. He designs and ships production-grade RAG systems and AI agents, and has hands-on experience with Java, Python, Go, and cloud-native DevOps for deep learning deployments. Sergey has contributed to AWS Deep Learning Containers by hardening build/test pipelines and addressing security and size-regression checks—work that improves reliability for widely used ML images. Based in the Atlanta metro area, he currently focuses on logistics engineering while mentoring and having taught over 500 engineers and testers, blending technical delivery with mentorship. His background in both economics and computer science gives him a pragmatic perspective on product impact and system trade-offs.
8 years of coding experience
7 years of employment as a software developer
Associate's degree, Computer Science, Associate's degree, Computer Science at Moscow Technical CollegeBachelor's degree, Economics, Bachelor's degree, Economics at Moscow Institute of International Economics Relationships
Stackoverflow
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Github Skills (7)
docker10
python10
dockers10
build-automation10
cicd10
testing9
aws9
Programming languages (2)
Github contributions (5)
aws/deep-learning-containers
Aug 2020 - Jan 2022
AWS Deep Learning Containers are pre-built Docker images that make it easier to run popular deep learning frameworks and tools on AWS.
Role in this project:
DevOps Engineer
DevOps EngineerContributions:1 release, 279 reviews, 76 commits in 1 year 5 months
Contributions summary:Sergey's contributions focused on enhancing the build and test infrastructure for the deep learning containers. They updated the image size check logic, ensuring that builds fail when images exceed baseline size limits. Additionally, they made adjustments to the test reporting and test coverage to ensure proper deployment and verification. The user also upgraded the urllib3 version to mitigate a security issue in the existing code.
pytorchsagemakercontainersmxnetserving
SergTogul/deep-learning-containers
Aug 2020 - Mar 2022
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.
Contributions:334 pushes, 132 branches in 1 year 7 months
caffe2trainingtensorflowawsserving
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