Sergey / backend engineer
RU
GitHub
Professional practice

Go backend, from profiling to deployment.

Go backend development across distributed audio processing, service integrations, and the infrastructure that makes them maintainable.

Download resume · PDF, Russian
Voice / ML / impact

Less work per chunk. Faster audio.

I profiled the processing path, removed bottlenecks and reduced audio chunk processing from 200 to 30 ms.

Audio chunk processing

Before200msAfter

Both bars use the same 200 ms scale. Reduction: (200 − 30) / 200 = 85%.

less processing time per audio chunk

15–20%

lower API latency after SQL and inter-service optimizations

Audio processing speedup

200 / 30 = 6.67×. Less processing time leaves more room in the audio pipeline’s latency budget.

Intent classification+Macro F1

I improved intent classification by 0.10 absolute Macro F1.

Entity extraction≈ +Entity F1

I improved entity extraction by approximately 0.10 absolute F1.

Structured output+5–6percentage points

I increased the share of responses with valid JSON structure by 5–6 percentage points.

Negation handling4×fewer errors / −75%

Reduced negation error frequency fourfold. The comparison is normalized to four units before and one after.

Experience

Go development, service performance and delivery.

Zuzex

Feb 2023 — Present

Backend developer

I develop Go services for distributed audio processing, contribute to architecture and code review, and own CI/CD pipelines.

  • Reduced audio chunk processing from 200 to 30 ms (85%) by profiling critical paths and removing bottlenecks.
  • Reduced API latency by 15–20% through PostgreSQL query optimization, less unnecessary I/O and improved inter-service communication.
  • Worked on gRPC streaming and Kafka / NATS service integrations; used OpenTelemetry, Prometheus and Grafana for observability.
  • Improved intent Macro F1 by 0.10 and entity F1 by approximately 0.10; increased JSON validity by 5–6 percentage points and reduced negation errors fourfold.
  • Configured Docker, unit tests, golangci-lint, artifact publishing, and deployment preparation.

Webpraktik

May 2022 — Jan 2023

Backend developer

REST APIs and external service integrations, backed by PostgreSQL and Redis. Containerized applications, wrote unit tests, and participated in code review and CI/CD.

Foundation

Don State Technical University — Mathematical support and administration of information systems, 2020–2024.

Russian — native. English — B2.

The engineering contextVoice / ML Platform