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| # Nikolay Dubina | |
| nikolay@ndx.one | |
| https://github.com/nikolaydubina | |
| https://www.linkedin.com/in/nikolaydubina | |
| ## Skills | |
| - Go, Python, Swift, C | |
| - GCP: GKE, BigQuery, PubSub, Firestore, App Engine, Cloud Storage, VertexAI | |
| - AWS: EKS, EC2, λ, SQS, SNS, Kinesis, Athena, EMR, SageMaker, S3, RDS, DynamoDB | |
| - Prometheus, Grafana, OpenTelemetry | |
| briefly worked with: Rust, Julia, Boost C++, LLVM, OpenMP, CUDA, Scala, Java Spring, Racket, Scheme, Lisp, Forth | |
| ## Experience | |
| ### [NDX](https://ndx.one) | |
| Senior Software Engineer, Founder | |
| Apr 2024 ~ present, HK | |
| - k8s cluster, Go, iOS Swift app, <1ms statistical spatial db, integrity, payment, auth, ai inference in GCP | |
| ### Motional | |
| Senior Software Engineer, Data Platform | |
| Jan 2024 ~ Apr 2024, SG | |
| - peta-scale data infrastructure for autonomous vehicles in Python, C++, Go | |
| - state-of-the-art stream processing algorithms in Go on k8s | |
| ### Zetta.ai | |
| Senior Software Engineer | |
| Dec 2023 ~ Feb 2024, US, Remote, Contract | |
| - peta-scale state-of-the-art neuroscience software | |
| - ground-up backend in Go + k8s cluster + frontend in Angular, GCP Firestore and App Engine | |
| ### DeliveryHero | |
| Senior Software Engineer, Payments | |
| Aug 2020 ~ Jan 2024, SG | |
| - built core backend payment systems handling 100% of revenue, 10s of millions USD/day, 10s of millions of users in 10+ countries | |
| - architecture, development, operations of backend in Go on k8s, MySQL, Redis, AWS SQS, EKS, S3, Terraform, DroneCI, NewRelic, Datadog | |
| - mentored interns and new hires, led projects of 20+ people, conducted 200+ interviews | |
| - promoted after one year to next level | |
| - two years of oncall shifts on Tier 1 | |
| ### Funding Societies | |
| Software Engineer, Platform | |
| Jan 2020 ~ Aug 2020, SG | |
| - maintained Kong API Gateway, stream processing services, upstream open source bug fixes in Go, Python, Node, Lua on ECS, PostreSQL in AWS | |
| - setup monitoring and automation on CircleCI, Datadog, Lambda | |
| ### Balancehero | |
| Lead Data Science and Engineering, Core Data | |
| Aug 2018 ~ Jan 2020, Seoul, KR | |
| - built alternative credit scoring model serving 200+ million people and operated it for 8+ months with industry standards | |
| - built batch data pipelines for feature processing, training, inference, evaluation, feature store, analytics in Spark, Python, Airflow, AWS EMR, Athena | |
| - built inference REST service in Python + Sagemaker | |
| - built data visualization for research and operational metrics in Airflow, H3, plotly, Tableau, Jenkins | |
| - built algorithms for efficient single node data processing in Python + joblib | |
| - built action rate predictive model, optimized promotion campaigns with A/B tests | |
| - researched state-of-the-art machine learning for [credit scoring](https://arxiv.org/abs/1905.03946) | |
| IC4 Software Engineer, Commerce Platform | |
| Aug 2016 ~ Aug 2018, London, GB | |
| - built commerce taxonomy classifier handling 100s of millions of samples producing 15K+ classes based on tabular, text, images data | |
| - built pixel based catalog creation; catalog feed rules; internal tools for debugging; and conducted research on elections integrity | |
| - development of backend (Hack, GraphAPI), frontend (React), offline and real-time data pipelines (Python, Scuba, Ent, Presto) | |
| - taught onboarding class on frontend, mentored new hires | |
| - promoted after one year to next level | |
| - oncall shifts | |
| - thousands of businesses relied on integrations I built | |
| Software Engineering Intern, Internal Tools | |
| May 2015 ~ Sep 2015, Menlo Park, US | |
| - refactored backend and frontend for internal legacy tools | |
| - made security enhancements for internal tools web-stack, Mercurial | |
| ### Enswers | |
| Software Engineering Intern, Infra | |
| Jan 2014 ~ Mar 2014, Seoul, KR | |
| - optimized in-memory data structures for better CPU cache performance and lower working set size in C++ | |
| - improved tooling for low level C++ profiling and testing | |
| ## Education | |
| BSc. Computer Science | |
| KAIST (Korea Advanced Institute of Science and Technology) | |
| 2012 ~ 2016, Daejeon, KR | |
| ## Professional Societies | |
| - Founding Member, Open Neuroscience Foundation, 2024 - present (tools development in Rust) | |
| ## Certifications | |
| - [Apple Ads Certified][1], 2026 | |
| - [CKA: Certified Kubernetes Administrator][2], 2023 | |
| - [CKAD: Certified Kubernetes Applications Developer][3], 2021 | |
| - [CLA: C Certified Associate Programmer][4], 2024 | |
| - [DAMA CDMP: Certified Data Management Professional][5], 2023 | |
| - [TOGAF: The Open Group Architecture Framework v9][6], 2023 | |
| - [PCA: Prometheus Certified Associate][7], 2023 | |
| - [Datadog: APM, Distributed Tracing, Logs, Fundamentals][8], 2023 | |
| - [HashiCorp: Terraform Associate][9], 2022 | |
| - [Redis: Certified Redis Developer x3][10], 2022 | |
| - [NVIDIA Accelerating End-to-End Data Science Workflows][11], 2021 | |
| - [NVIDIA Accelerating CUDA C++ Applications with Concurrent Streams][12], 2021 | |
| - [NVIDIA Scaling Workloads Across Multiple GPUs with CUDA C/C++][13], 2021 | |
| - [NVIDIA Fundamentals of Accelerated Computing with CUDA C/C++][14], 2021 | |
| - [NVIDIA Fundamentals of Accelerated Computing with CUDA Python][15], 2021 | |
| - [GCP Professional Data Engineer][16], 2021 | |
| - [AWS DevOps][17], 2021 | |
| - [AWS Data Analytics][18], 2020 | |
| - [AWS Database][19], 2020 | |
| - [AWS Machine Learning][20], 2019 | |
| - [University of Washington (coursera) Machine Learning][21], 2017 | |
| ## Open Source | |
| trending on GitHub multiple times in 2024/2025 | |
| - https://github.com/nikolaydubina/go-recipes collection of useful commands for Go projects, 4450 ⭐️ | |
| - https://github.com/nikolaydubina/go-cover-treemap tool to make treemaps for Go test coverage, 486 ⭐️ | |
| - https://github.com/nikolaydubina/go-binsize-treemap tool to make treemaps for Go binaries, 444 ⭐️ | |
| - https://github.com/nikolaydubina/go-instrument automatically add OpenTelemetry instrumentation to Go functions, 288 ⭐️ | |
| - https://github.com/nikolaydubina/go-hackers-delight showcase of code from notorious "Hackers Delight", 117 ⭐️ | |
| - https://github.com/Kong/kong bugfix (v2.1.1), Lua | |
| - https://github.com/json-iterator/go bugfix, Go | |
| - ... and many more | |
| ## What I Have Read on Software | |
| - All of Clean Code series: Clean Coder, Clean Code, Clean Architecture, Clean Craftsmarnship, Robert.C.Martin, Addison-Wesley | |
| - Refactoring series: Refactoring; Refactoring Database;, Addison-Wesley | |
| - The Linux Programming Interface, Addison-Wesley | |
| - DNS and Bind, IPv6, CoreDNS, O'Reilly | |
| - Strategic Monoliths and Microservices, Addison-Wesley | |
| - Patterns for API Design, Addison-Wesley | |
| - Visual Models for Software Requirements, Microsoft, Addison-Wesley | |
| - Domain Storytelling, Addison-Wesley | |
| - Continuous Architecture in Practice, Addison-Wesley | |
| - DAMA-DMBOOK: Data Management Body of Knowledge | |
| - Learn Grafana 7.0, Packt | |
| - Hands-On Infrastructure Monitoring with Prometheus, Packt | |
| - Prometheus Up \& Running, O'Reilly | |
| - CKA Study Guide; CKAD Study Guide, O'Reilly | |
| - Code That Fits in Your Head, Robert.C.Martin | |
| - Software Engineering at Google, O'Reilly | |
| - How Google Tests Software, Addison-Wesley | |
| - Understanding Software Dynamics, Addison-Wesley | |
| - Terraform: Up and Running, O'Reilly | |
| - HashiCorp Infrastructure Automation Certification Guide, Packt | |
| - Continuous Delivery: Reliable Software Releases Through Build, Test, and Deployment Automation, Addison-Wesley | |
| - Software Architecture: The Hard Parts: Modern Tradeoff Analysis for Distributed Architectures, O'Reilly | |
| - Modern Software Engineering: Doing What Works to Build Better Software Faster, Addison-Wesley | |
| - Design It!: From Programmer to Software Architect, Pragmatic Programmers | |
| - Kubernetes Up and Running, O'Reilly | |
| - gRPC Up and Running, O'Reilly | |
| - Systems Performance, Addison-Wesley | |
| - Working Effectively with Legacy Code, Michael C.Feathers | |
| - Expert Hadoop Administration: Managing, Tuning, and Securing Spark, YARN, and HDFS, Addison-Wesley | |
| - Large-Scale C++ Volume I: Process and Architecture, Addison-Wesley | |
| - Domain-Driven Design Quickly, Infoq | |
| - The Hundred-Page Machine Learning Book | |
| - Machine Learning in Production, Addison-Wesley | |
| - Gnu Make Reference Manual, Richard Stallman | |
| - Pro Git | |
| - Mastering PostgreSQL 12, Packt | |
| - Modern Data Mining Algorithms in C++ and CUDA C | |
| - The Art of UNIX Programming, Addison-Wesley | |
| - BPF Performance Tools, Addison-Wesley | |
| - Advanced Programming in the UNIX Environment, Addison-Wesley | |
| - Design Patterns: Elements of Reusable Object-Oriented Software, Addison-Wesley | |
| - Designing Distributed Systems, O'Reilly | |
| - The Go Programming Language, Addison-Wesley | |
| - Cloud Native Infrastructure, O'Reilly | |
| - Site Reliability Engineering: How Google Runs Production Systems, O'Reilly | |
| - The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling | |
| - Designing Data-Intensive Applications, O'Reilly | |
| - ... and many more | |
| ## What I Have Read on Neuroscience | |
| - Principles of Neurobiology, Liqun Luo | |
| - Principles of Neural Science, Eric R. Kandel | |
| - Fundamental Neuroscience, Larry R. Squire | |
| - From Neuron to Cognition via Computational Neuroscience, Michael A.Arbib | |
| - Brain-Computer Interface Research: A State-Of-The-Art Summary, Christoph Guger, Springer | |
| - Neuroscience of Mathematical Cognitive Development, Rhonda Douglas Brown, Springer | |
| - Emergent Brain Dynamics: Prebirth to Adolescence, April Benasich, Strüngmann Forum | |
| - Translational Neuroscience: Toward New Therapies, Karoly Nikolich, Strüngmann Forum | |
| - The Neocortex, Wolf Singer, Strüngmann Forum | |
| - Connectome: How the Brain's Wiring Makes Us Who We Are, Sebastian Seung | |
| - Changing Connectomes, Marcus Kaiser, MIT Press | |
| - Brain Computation as Hierarchical Abstraction, Dana H. Ballard, MIT Press | |
| - All of Oliver Sacks books | |
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