Pavel Shmakov
Senior Machine Learning Engineer, Research at PhysicsX
London, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolPavel Shmakov is a Senior Machine Learning Engineer and research-oriented software engineer with about a decade of experience spanning Google (five years), startups and scientific research, and a PhD in theoretical physics. He builds high-performance numerical and distributed systems—having implemented PDE solvers in the popular tf-quant-finance project and optimized core financial algorithms from O(n^2) to O(n)—and combines low-level C++ and TensorFlow work with cloud-native GCP tooling. Equally comfortable in backend, Android, and full-stack roles, he has shipped Trusted Web Activities for Chrome and led tech-debt reduction efforts at scale. Pavel favors well-designed, well-tested code and proactively drives maintainability and debt reduction while working at the intersection of science and engineering. Based in London, he brings uncommon depth from theoretical physics into practical ML and scientific computing solutions.
10 years of coding experience
11 years of employment as a software developer
Saint Petersburg State Electrotechnical University "LETI"
English
Github Skills (16)
kotlin10
chrome-custom-tabs10
finance10
javas10
code-generation10
android-sdk10
tensorflow10
python10
android10
dependency-injection10
android-development10
java10
quantitative-finance10
obfuscation9
apidoc7
Programming languages (5)
Github contributions (5)
google/tf-quant-finance
Nov 2019 - May 2022
High-performance TensorFlow library for quantitative finance.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:55 commits, 5 comments in 2 years 6 months
Contributions summary:Pavel implemented and enhanced PDE solvers within the tf-quant-finance library, contributing to the development of a high-performance TensorFlow library for quantitative finance. They added a v2 of PDE solvers, including multi-dimensional solvers and boundary condition support. Moreover, the user implemented the GenericItoProcess.fd_solver_backward() and forward functions, extending the library's capabilities for solving PDE equations associated with Ito processes, as well as incorporating the Fokker-Planck equation.
pythonautomatic-differentiationnumerical-optimizationtensorflowfinance
GoogleChrome/custom-tabs-client
Oct 2018 - Jul 2019
Chrome custom tabs examples
Role in this project:Mobile Developer (Android)
Mobile Developer (Android)Contributions:20 commits in 9 months
Contributions summary:Pavel primarily contributed to the Android-specific implementation of the custom tabs client. Their work involved adding functionality for retrieving and managing small icon bitmaps for notifications, enabling the launching of Chrome's site settings for managing data related to Trusted Web Activities (TWAs), and updating the LauncherActivity to work well in the "Single Activity TWA" mode, along with adjustments for splash screens and dark mode integration. The user also made code adjustments for TWA compatibility with Chrome versions.
chrome-custom-tabschromecustom-tabstabschrome-extension
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