Systems Software Engineer

* Optimized hot code paths in behavioral prediction modules, achieving **up to 60%** decrease (**~2000 to 800 ns** on local i5-11 machine) in simulation step times; * Optimized memory throughput by implementing RCU-based lock-free caching, resulting in a measurable reduction in CPU contention of **up to 50%** in certain scenarios; * Optimized CI pipeline jobs by introducing and troubleshooting Github Actions caches populated with compiler-generated artifacts, reducing average build job time **from 20 to 4 minutes**; * Reduced state sync delays **by ~3 times** in average by implementing and plugging in custom EVM glue for on-the-node batch processing; * Introduced AI-assisted debugging (via Devin) and performance analysis, improving engineering leading to the team’s increase of debugging and optimization task efficiency indicators by **at least 30%**; * Prevented **a whole class of regressions** by introducing a Zstd-compressed time-series fixture format in Git LFS, enabling mandatory CI runs of integration tests which previously depended on archive node availability; * Balanced throughput and latency by fine-tuning the scheduling of CPU-bound (Rayon) and I/O-bound (Tokio) task OS threads side by side, increasing success rate of multihop swap opportunities by **5–10%**; * Drove architectural discussions focused on scalability, maintainability, and technical debt reduction, mentoring **2 developers** on project architecture and general low level practices.

* Eliminated recurring production outages by identifying and resolving a complex cross-language Rust/C memory corruption issue, saving approximately **~20 engineering hours** spent on 30+ intermittent production downtime incidents **per week**; * Reduced mass-deployment hardware costs by **up to 60%** by reverse-engineering proprietary access point boot processes, enabling large-scale deployment of the lower-cost networking devices; * Developed and deployed a custom OpenWRT-based firmware platform enabling centralized, billable Wi-Fi services across **400+** commercial/retail locations with no single point of failure; * Implemented a zero-downtime A/B firmware update system, enabling seamless over-the-air upgrades for **2500+** devices, ensuring uninterrupted service for end-users; * Enabled centralized monitoring and remote management of near **95%** of device functionality by building a comprehensive backend API layer for the customer dashboard.

* Engineered ultra-low-latency execution and market data adapters for multiple centralized exchanges using WebSocket, FIX 4.4, and REST APIs, optimizing throughput to handle **5–10K+ events/sec**; * Reduced mean time to resolution (MTTR) for performance regressions by **up to 70%** by architecting a comprehensive distributed tracing framework using OpenTelemetry across asynchronous services; * Reduced p99 latency by **20–30%** across latency-critical trading workflows by identifying CPU bottlenecks and eliminating lock contention through performance profiling.

* Engineered high-throughput networking packet processing pipelines, sustaining **10+ Gbps** line-rate traffic, using Rust, modern C++, DPDK, and zero-copy architectures; * Identified and reduced CPU cache invalidations and pipeline stalls through rigorous profiling and memory layout optimization, achieving **up to 15–20%** performance gains on certain production workloads; * Fixed **optimization-breaking UB** from C-style type punning by backporting a standard-compliant `std::bit_cast` polyfill for GCC 10 that respects C++ strict aliasing and object lifetime rules; * Improved efficiency of matcher primitives by **up to 30%** by facilitating copy elision and replacing heap collection references with view types for implicit argument conversions; * Reduced networking layer code duplication by **6–8%** and improved maintainability by modernizing legacy components with reusable, type-safe C++20 templates and concepts.

* Built a highly parallelized counterfactual regret minimization (CFR) engine from the ground-up, **delivering a core distributed backend** for large-scale game theory simulations under heavy confidentiality constraints; * Orchestrated cloud infrastructure for complex ML training workflows, utilizing Amazon APIs and automation tools to **dynamically spin up and configure** optimized cloud instances; * Reduced AWS EC2 compute overhead by **~30%** through deep profiling and elimination of cross-node NUMA bottlenecks in a highly concurrent solver training workload; * Streamlined historical data reconciliation by implementing an automated batch ELT workflow with ClickHouse as persistence backend, reducing snapshot processing latency by **98–99%**.

* Implemented a dynamic pricing and automatic client suspension module for cEnergo smart metering system, orchestrating its operation with **8** existing business logic modules (metering device accounting, measurement streaming, state synchronization etc.), each with its own model-level interface; * Ported an MCU-based bare metal firmware codebase to a Linux-based platform in **under a month**; * Reverse engineered a proprietary smart card based billing protocol by capturing USB packets exchanged by a rebranded in-browser ActiveX control with specific non-PC/SC (`T=14`) card reader models; * Implemented stable remote firmware update reflashing onto raw MTD partitions with thorough integrity checks; * Implemented a comprehensive REST-based API endpoint in smart metering system for foreign clients.