SWE & AI/ML, EE/CS @ UCSC

MartinMuskov

Lead Software Engineer @ Credda, Inc., and an electrical engineering and computer science student at UC Santa Cruz.

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01

About

I am reading for a B.S. in Electrical Engineering at UC Santa Cruz, with a planned minor in Computer Science. My interests are software engineering, artificial intelligence and data engineering.

Outside the degree I build my own things, mostly systems software written to be checked rather than asserted: compilers, consensus, storage engines, execution caches. Where a project makes a correctness claim, a test in the repository tries to break it. I am always looking for work that stretches what I can do.

02

Work

  1. Lead Software Engineer & CTO @ Credda, Inc.

    Apr 2026 — present

    San Francisco, California · In-Person

    Co-founder. Credda is an AI-driven software engineering platform that turns a bug report into a patch.

    • Created the patch engine end to end: it replicates the reported error, localizes the root cause, generates the repair and validates the whole process automatically.
    • Built the backend infrastructure and the artificial intelligence pieces that keep the platform running.
    • Implemented the CLI, GitHub Action and client SDKs that customers use to run Credda inside their own CI workflows, so their source never leaves their environment.
  2. Software Engineer Intern @ Converge Insurance

    Jun — Aug 2026

    San Francisco, California · Hybrid

    The Data Fluency Initiative: the reporting and data tooling behind underwriting, actuarial, insurance operations and product.

    • Co-developed the Converge BI underwriting dashboard, which brought scattered requests into one report. Designed the filters, views and chart types around what each team needed, then validated every figure in it against the actuarial team's independently calculated numbers and ran down the differences.
    • Analysed the historical submission and policy data independently, which turned up two errors in the underlying data and in the forecasting model, both corrected before any conclusion was drawn. Delivered a written report on broker and segment performance against loss ratio and retention, with a premium forecast for the coming period.
    • Improved the triage severity model, and established that its reliability is bounded by how few medium- and high-severity claims are labelled at all. Investigated ways to make the confidence an LLM reports about its own answer mean something.
03

Education

  1. EE/CS @ UCSC

    Sep 2025 — present

    Santa Cruz, California

    B.S. Electrical Engineering, with a planned minor in Computer Science.

05

Stack

Languages
GoRustJavaPythonTypeScriptKotlin
Web
ReactNext.jsTailwind
Systems & infra
DockerAWSTerraformPostgreSQL
Focus
CompilersAutodiffMachine learningDistributed systemsBuild systemsVerifiable credentials
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Contact