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Anton Penkov

Anton Penkov — Novi Sad, Serbia

Nuclear engineering, AI evaluation, and two apps of my own.

It is more coherent than it looks. All of it is the same problem — making sure complex technical work is actually correct — approached from a different side each time: as the engineer producing it, as the operation that makes 150+ people produce it, and as the only person responsible when I ship something myself.

Two apps I built for myself, on the App Store
Anton Penkov, AI Data Operations · iOS Developer
engineers coordinated
150+engineers coordinated
review cycles analysed
200+review cycles analysed
apps on the App Store
2apps on the App Store
in nuclear engineering
6 yrsin nuclear engineering
languages shipped
7languages shipped
01Through-line

The same problem, from every side.

Produce the work. Prepare the data. Run the operation. Fix it when it breaks. Then own all of it at once.

  1. Produce it

    Nuclear piping design

    Six years designing piping systems for nuclear power facilities, where every decision had to be calculated, documented and defended before anything was built.

    Rosatom · 2016—2022

  2. Prepare it

    Data preparation

    Structured data for technology products, inside workflows where consistency is the thing that decides whether the output is any good.

    ABBYY · 2022—2024

  3. Run it at scale

    AI data operations

    Workforce and delivery operations for a programme producing agentic coding-evaluation data: 150+ engineers, 20+ reviewers, and 200+ review cycles traced back to 12 root causes.

    Toloka AI · 2025—now

  4. Fix it when it breaks

    Incident resolution

    Complex operational and technical incidents owned end to end — reproduce, trace through the systems involved, pull in whoever can fix it, stay through escalation.

    Emerging Travel Group

  5. Own all of it

    Two iOS apps

    Designed, written, localised, shipped and maintained by one person. Every decision mine, and every mistake too.

    Jarz · NoRep

02Selected work

Two apps on the App Store.

Not client work — these are the two I had wanted to build for years, then finally did. Designed, developed and released on my own: data model, interface, localisation, submission, and everything that comes after.

Jarz

Salary Planner

A salary planner, not an expense tracker.

Every payday you split your income into jars — food, rent, bills, savings — and every purchase comes out of its jar. At any moment the app answers one question: what can I still afford?

The food jar works as a daily rate. Set an amount per day and Jarz sets aside a month of it on payday, then shows what is left for today and how many full days are still covered. Everything stays on device and syncs through the user’s own private iCloud.

Finance · iOS 17+ · Free · 7 languages

  • Swift
  • SwiftUI
  • SwiftData
  • CloudKit
  • WidgetKit
  • Clean Swift (VIP)
  • XcodeGen
  • Jarz home screen showing the remaining food budget for today and the balance of every jar
  • Jarz income screen distributing a salary across jars, with fixed costs pre-filled automatically
  • Jarz revision screen comparing the planned balance against money counted on cards and in cash

NoRep

WOD & HIIT Timer

A workout timer that keeps up with the workout.

EMOM, AMRAP, For Time and Tabata, plus a Mix builder that chains blocks and rests into a single WOD. The workout text stays on screen while the clock runs, so you always know what is next.

The timer is anchored to the wall clock rather than a tick loop, which keeps it exact through pauses and backgrounding. Rounds are timestamped into a journal that tracks splits, streaks and personal records, and the whole thing runs on the Apple Watch too.

Health & Fitness · iOS 17+ · Free · Apple Watch

  • Swift
  • SwiftUI
  • SwiftData
  • CloudKit
  • Live Activities
  • watchOS
  • HealthKit
  • Clean Swift (VIP)
  • NoRep home screen listing the EMOM, AMRAP, For Time, Tabata and Mix timer modes
  • NoRep running an EMOM round with a circular countdown dial and the current movement shown above it
  • NoRep journal showing a day streak, a twelve-week activity heatmap and a list of finished workouts
03Experience

Experience

The same story in order, with the detail the summary above leaves out.

  1. 2025 — Present

    Toloka AI

    Workforce Operations & Quality Lead

    SDLC programme — agentic coding-evaluation data for a frontier AI lab

    I run the workforce and delivery side of a programme producing LLM evaluation testcases — the layer that gets a large distributed group of engineers to turn out work on time and to standard, and finds out where it is breaking when they do not. Most of the tooling that layer runs on, I built.

    • Coordinated 150+ software-engineering experts and 20+ QA reviewers across the full lifecycle — onboarding, access provisioning, production support, offboarding.
    • Built the AI-assisted operations tooling: automated Discord, GitHub and Databricks analytics pipelines for support-queue dashboards, throughput and seed-readiness tracking, and bulk evidence verification with LLM agents. Multi-day manual audits became hours.
    • Ran payment-integrity and reviewer-calibration investigations: volume-versus-quality audits of top-earning reviewers, with minimal audit samples built by set-cover analysis so a six-person senior team could verify 25+ people against a hard deadline.
    • Root-cause work on rejected output: analysed 200+ review cycles across 120+ deliverables, grouped the causes into 12 recurring themes, and turned those into tooling checks, instruction rewrites and reviewer calibration — an action plan targeting a 2.5× reduction in rework.
    • Led client-mandated security-compliance campaigns — passkey enforcement across the entire expert pool with per-account verification, VPN-usage enforcement, and fraud-network referrals including identity re-verification and referral-chain tracing.
    • First-line escalation for expert technical blockers: diagnosed CI and infrastructure failures, routed them to platform owners, and wrote the playbooks that turned recurring incidents into five-minute resolutions.
    • Designed and ran the communications and incentive programmes — release announcements, bonus schemes, a mentorship framework and a QA promotion track.
    • Workforce operations
    • Delivery management
    • AI evaluation data
    • Ops tooling
  2. Present

    Remote

    Emerging Travel Group

    Incident Resolution Specialist / CTM

    Own complex operational and technical incidents end to end: reproduce the problem, trace it through the systems involved, pull in the teams that can fix it, and stay with it through escalation. Most of the work is narrowing down what actually went wrong before anyone can act on it.

    • Incident resolution
    • Troubleshooting
    • Cross-functional work
  3. 2023 — Present

    Part-time

    SwiftBook

    iOS Developer

    Build iOS applications with Swift, UIKit and SwiftUI alongside a structured curriculum covering interface, networking, persistence and architectural patterns.

    • Swift
    • UIKit
    • SwiftUI
  4. 2022 — 2024

    ABBYY

    Data Preparation Specialist

    Prepared and quality-checked structured data for the company’s technology products, working inside data workflows where consistency directly determines how good the output is. This is where the move from engineering into technology and AI started.

    • Data preparation
    • Data quality
    • Structured workflows
  5. 2016 — 2022

    Rosatom

    Nuclear Piping Design Engineer

    Designed piping systems for nuclear power facilities and produced the technical documentation behind them. Six years of work where every decision had to be calculated, documented and defended before anything was built — which is still how I approach software.

    • Engineering design
    • Technical documentation
    • Complex systems

Education

Moscow Power Engineering Institute (MPEI)

Master’s degree — Nuclear Engineering / Nuclear Physics2016 — 2018

04About

How it actually fits together.

I started in nuclear engineering — six years designing piping systems for nuclear power facilities. Precise, heavily documented work, where you learn to think in whole systems and to check yourself long before anyone else does.

Then data preparation at ABBYY, and now Toloka, where I run workforce and delivery operations on a programme producing agentic coding-evaluation data for a frontier AI lab. The scale changed — 150+ engineers rather than one drawing — but the question did not: is this getting done properly, and if not, where exactly is it breaking.

The two iOS apps began as something I had wanted to do for years, so I learned Swift and did it — two apps on the App Store, designed, written, localised and released by me. Nobody asked for them, which is rather the point. That habit turned out to be the useful part of the job as well: most of the operations tooling I depend on at work I built myself. I would rather build the thing that answers a question than wait for it to come back as a ticket.

None of this was a plan. But standing at each position in turn — producing the work, checking it, running the people who do both, and then doing all of it alone — turns out to be a useful way to understand why technical work goes wrong.

05Technologies

Technologies

Everything here is used in shipped or published work.

Language & UI
  • Swift
  • SwiftUI
  • UIKit
  • async/await
Data & networking
  • SwiftData
  • CloudKit
  • Realm
  • URLSession
  • REST
  • JSON
Apple platform
  • iOS SDK
  • WidgetKit
  • Live Activities
  • watchOS
  • HealthKit
Architecture & tooling
  • Clean Swift (VIP)
  • MVC
  • Xcode
  • XcodeGen
  • Git
  • App Store Connect
Operations tooling
  • Databricks
  • GitHub API
  • Discord API
  • LLM agents
06Earlier work

Earlier work

Smaller projects and coursework from while I was learning. Kept for completeness — the two apps above are the better evidence.

Learning projects

  • SwiftQuiz

    A quiz app for learning Swift, built as a team project.

    UIKit · MVC · UITableView · Storyboard

  • ChicagoArt

    A browser for the Art Institute of Chicago’s public collection API.

    URLSession · Alamofire · Kingfisher · UIKit · MVC

  • To Do List

    Task list backed by a local Realm database.

    Realm · iOS

  • Personal Finance

    Budget tracker with custom categories and multiple currencies.

    SwiftUI

  • ChatAI

    A small chat client built on the ChatGPT API.

    Swift · REST

Certifications — SwiftBook

  • Basics of Swift ProgrammingOct 2023
  • User Interface. UIKitJan 2024
  • Data and NetworkFeb 2024
  • SwiftUIMar 2024
  • Preparing for interviews and job searchesApr 2024
  • Architectural PatternsMar 2025
  • Junior iOS-DeveloperMar 2025
07Contact

Let’s build something useful.

Open to conversations about AI data operations, about iOS, and about hard problems generally. Email is the surest way to reach me.