Kiril Zlatkov
San Francisco, California, United Arab Emirates
Summary
🤩
Rockstar🎓
Top SchoolKiril Zlatkov is an analytical data and product leader with 10 years of experience driving business performance at top-tier tech and finance companies, including Google, Amazon, Kraken, and HPE. He builds and scales business intelligence platforms and teams that translate complex data into actionable insights for senior leaders, enabling data-driven decisions across product, finance, and operations. Comfortable bridging engineering and analytics, he has hands-on experience in back-end and DevOps contributions to high-profile open-source projects like TensorFlow Serving. An INSEAD MBA and dual-background in computer science and economics underpin his ability to combine technical depth with commercial strategy. Based in San Francisco with international experience in the UAE, he’s known for simplifying complexity and delivering measurable impact across global organizations.
10 years of coding experience
11 years of employment as a software developer
Master of Business Administration (MBA), Master of Business Administration (MBA) at INSEADBachelor's degree Computer Science Economics, Bachelor's degree Computer Science Economics at American University in BulgariaAmerican College of Sofia
Stackoverflow
171reputation
7kreached
4answers
0questions
Github Skills (16)
c-language10
deep-learning10
cpp10
tensorflow10
cprogramming-language10
serve10
grpc10
python9
machine-learning9
json6
docker6
bazel6
tensorflow-serving6
numpy6
protocol-buffers6
Programming languages (3)
Github contributions (5)
tensorflow/serving
Feb 2016 - Feb 2018
A flexible, high-performance serving system for machine learning models
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:6 releases, 345 commits, 194 PRs in 2 years
Contributions summary:Kiril primarily focused on migrating the project to use gRPC 0.13 and the latest version of TensorFlow. This involved modifying various C++ and Python files, specifically related to the MNIST example, to incorporate the updated gRPC and TensorFlow dependencies. The changes include modifications to protobuf files and gRPC service definitions. The user also made internal changes, which most likely included updates to test files and utilities.
cpppythonservingdeep-learningml
kirilg/serving
Feb 2016 - Feb 2018
Contributions:1 PR, 17 pushes, 79 branches in 1 year 11 months
servingmachine-learningperformancehigh-performancemachine-learning-models
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