Anna Khanova

Zurich, Zurich, Switzerland

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Summary

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Rockstar

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Top School

Anna Khanova is a software engineer based in Zurich with eight years of industry experience and a recent focus on integrating machine learning into complex infrastructure. She has shipped production systems at big tech firms including Google and contributed to serverless database and ML library projects like Neon and CatBoost, improving proxy resilience and .NET resource management. Her background spans Cloud Conversational AI quality work and hands-on backend development, demonstrating both customer-facing product sensitivity and low-level systems rigor. Colleagues value her for clear communication and collaborative drive toward shared goals. Notably, she implemented configurable timeouts and IP allowlisting for Neon’s serverless Postgres proxy—small changes that materially improved reliability and security at scale. She trained in AI at Yandex School of Data Analysis and holds a strong computer science foundation from Ural State University.

8 years of coding experience

4 years of employment as a software developer

Bachelor's degree, Computer Science, 4.9 out of 5.0, Bachelor's degree, Computer Science, 4.9 out of 5.0 at Ural State University named after A.M.Gorky

Artificial Intelligence, 4.3 out of 5.0, Artificial Intelligence, 4.3 out of 5.0 at Yandex School of Data Analysis

Russian, English, German

Github Skills (27)

postgresql10

net10

dotnet10

asp-net10

dotnet-core10

rust10

csharp10

catboost9

gradient-boosting9

machine-learning9

http9

databases9

sql-database9

database9

relational-databases9

Programming languages (6)

C#SmartyC++CRustJavaScript

Github contributions (5)

neondatabase/neon

Oct 2023 - Jul 2024

Neon: Serverless Postgres. We separated storage and compute to offer autoscaling, code-like database branching, and scale to zero.

Role in this project:

Back-end Developer

Contributions:206 reviews, 134 PRs, 312 pushes in 9 months

Contributions summary:Anna primarily focused on improving the Neon serverless Postgres database proxy functionality. Their contributions included adding timeouts for HTTP requests, making the HTTP timeout configurable via CLI arguments, and fixing issues with JSON array handling. Furthermore, the user worked on setting up timeouts for the SCRAM protocol execution and introducing IP allowlist filtering on the proxy side. These changes enhance the proxy's resilience, configuration, and security features.

neonrustserverlessautoscalingoffer

catboost/catboost

Mar 2020 - May 2020

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Role in this project:

Backend & QA Engineer

Contributions:9 commits, 6 PRs, 3 comments in 1 month

Contributions summary:Anna primarily contributed to the .NET implementation of the CatBoost library. Their work involved implementing the `IDisposable` interface for proper resource management, indicating a focus on code cleanup and preventing memory leaks. They fixed several incorrect statements within the code, and also addressed and fixed broken tests for the .NET implementation. Additionally, they introduced new methods for the interface, suggesting involvement in feature enhancements and model evaluation improvements.

kagglexgboostpythondata-mininglightgbm

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