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OpenTrain AI

Snr Code Reviewer - Java

OpenTrain AI · Remote · Worldwide · Posted Jun 6, 2026

Apply for this job Hourly · $25/hr

About OpenTrain

OpenTrain is a central job board for data-labeling and AI-training work, aggregating openings from many companies and platforms so candidates can find labeling roles in one place. Creating an OpenTrain account is free and applying takes only a few minutes.

We connect specialists with short- and long-term projects that help build better AI systems by supplying high-quality human-reviewed data.

About AI Training Work

AI training (also called data labeling or human feedback work) is the human side of building machine intelligence: people annotate, run, and rate examples that models learn from.

This role focuses on evaluating AI-generated code and the human annotations that judge it—work that directly shapes how next-generation coding assistants and developer tools behave.

The Role

You will audit annotator evaluations of AI-generated Java code: compile and run each snippet in an isolated environment, verify it satisfies the prompt, confirm correct behavior, assess security and performance, and correct mis-ratings.

This is a remote, contractor role (part-time) at $25 USD per hour, requiring 20+ hours per week. Open to applicants worldwide.

  • Position: Senior Java Code Reviewer (contract, part-time)
  • Rate: $25 USD per hour (pay-per-hour)
  • Time: 20+ hours/week
  • Location: Remote — worldwide applicants welcome

What You’ll Do

Your primary responsibility is to ensure the quality and consistency of code-review annotations produced by human annotators. You will compile and run submitted Java snippets in sandboxed or containerized environments, reproduce issues, and verify functional correctness against the prompt.

You will apply secure-coding and performance best practices, correct incorrect ratings, provide concise written feedback aligned to a rubric, and escalate ambiguous or high-risk cases.

  • Audit annotator evaluations of AI-generated Java responses and correct mis-ratings.
  • Compile and run code in isolated sandboxes or containers to validate behavior and prompt compliance.
  • Check for secure-coding issues (OWASP-top-10, deserialization, injection, permission flaws).
  • Assess JVM performance expectations, GC/JIT behavior, and profiling where required.
  • Evaluate concurrency and multithreading correctness (locks, race conditions, CompletableFuture, reactive streams).
  • Provide concise, rubric-aligned feedback and mentoring comments for annotators.
  • Log findings and decisions in ticketing/annotation tools and follow checklist-driven QA workflows.

Requirements

You must meet every substantive technical requirement listed below. We will expect evidence of hands-on experience and the ability to reproduce/validate code in an isolated environment.

  • 7+ years of professional Java development, QA, or dedicated code-review experience.
  • Deep expertise in modern Java (11–21), core APIs, and JVM internals.
  • Strong knowledge of JVM performance tuning (GC, JIT, profiling) and performance expectations.
  • Advanced testing and debugging experience: JUnit 5, TestNG, Testcontainers, Mockito, and coverage tools (e.g., JaCoCo).
  • Proven ability to analyze concurrency and multithreading: thread safety, locks, CompletableFuture, Project Reactor/RxJava.
  • Secure-coding expertise: spot and mitigate OWASP Top 10 issues, deserialization attacks, injections, and race conditions.
  • Familiarity with build and toolchain: Maven/Gradle, Dockerized builds, CI/CD (GitHub Actions, GitLab CI).
  • Comfort compiling and running code in sandbox or container environments to validate functionality and prompt compliance.
  • Experience with structured QA: rubric-based scoring, checklist-driven reviews, and ticketing tools (Jira, Asana).
  • Excellent written English (B2+ CEFR) for concise feedback and reports.

Who Should Apply

This role suits senior Java engineers, experienced code reviewers, and QA specialists who enjoy hands-on debugging, secure-coding analysis, and mentoring annotators through concise feedback.

Candidates with prior exposure to AI/ML annotation work, LLM evaluation, or RLHF pipelines are especially welcome but not required.

  • Senior Java developers who like focused, part-time remote work.
  • Code reviewers and QA engineers comfortable with rubric-driven evaluations.
  • Applicants who can balance technical depth and clear written communication.
  • Nice to have: past work on LLM evaluation, RLHF, or other AI/ML data-labeling projects.

How It Works

If you’re selected, you’ll join a structured QA workflow: receive examples, run them in isolated environments, apply the rubric, and submit corrected ratings and concise feedback via our annotation tools and ticketing system.

OpenTrain aggregates AI-training roles and will guide you through account creation and the quick application process. Compensation is hourly at the stated rate and paid per the project’s contractor terms.

  • Apply via OpenTrain (free account, minutes to apply).
  • Work remotely; use containerized sandboxes or provided environments to validate code.
  • Follow rubric and checklist for every review; record decisions in ticketing tools.
  • Contractor engagement, part-time schedule, paid hourly at $25 USD.