Snr Code Reviewer - Go

About OpenTrain

OpenTrain aggregates data-labeling and AI-training jobs from many AI companies and labeling platforms into one place so candidates can discover this kind of work without hunting dozens of sites.

Creating an OpenTrain account is free and applying to jobs on the platform typically takes only a few minutes.

About AI training and code-review work

AI models learn from examples prepared and reviewed by people. For code-related projects that means humans evaluate model-generated code, check correctness, safety, and performance, and provide feedback that teaches models to produce better outputs.

This project focuses on auditing human annotators who reviewed AI-generated Go code: your reviews will directly improve training data used to teach next-generation models how to write safe, efficient Go.

• Work is fully remote and typically flexible in schedule for part-time contributors.
• Contributions shape model behavior, quality, and safety for real-world developer workflows.

The role

Title: Senior Go Code Reviewer. You will audit annotator reviews of AI-generated Go code responses by compiling and executing submitted snippets in a sandboxed environment, confirming they satisfy the prompt, function correctly, and meet secure coding and performance standards.

You must identify and correct any mis-ratings, provide clear, actionable feedback, and ensure each review adheres to the project's quality rubric so training data remains accurate and safe.

• Employment type: Contractor, Part-time.
• Time requirement: 20+ hours per week.
• Pay: Hourly, USD $24 per hour.
• Work scope: AI-generated Go code response annotation; labeling software: Other.
• Role tag: subject matter is AI-generated Go code response annotation.

What you'll do

Perform hands-on validation of code submissions: build and run snippets in sandboxed environments to confirm functional compliance with the prompt and expected outputs.

Assess reviews against the quality rubric: check correctness, safety, performance, and the accuracy of annotator ratings, correcting mis-ratings with step-by-step, constructive feedback.

• Compile and execute Go 1.18+ code safely in sandboxes and reproduce reported behaviors.
• Verify prompt compliance and confirm that solutions meet functional requirements.
• Evaluate concurrency, memory-safety, and performance patterns (goroutines, channels, select, mutexes).
• Check error handling, race conditions, dependency vulnerabilities, and secure coding practices.
• Provide clear, actionable feedback and remediation steps for annotators.
• Score reviews using rubric-based checklists and create or update tickets as needed.

Requirements

The listing tags this role as Intermediate, and the ideal qualifications reflect a senior-level reviewer: please read both carefully to ensure a match.

All required skills and qualifications below are drawn from the project brief and must be met or demonstrated in your application.

• Experience: 5–7+ years in professional Go development, QA, or dedicated code-review roles.
• Go mastery: Deep knowledge of Go 1.18+ (generics, modules, standard library, build tooling).
• Concurrency & performance: Proven expertise with goroutines, channels, select, mutexes, and profiling tools (pprof, trace).
• Testing & debugging: Advanced use of testing package, table-driven tests, benchmarks, and the race detector.
• Secure coding: Ability to detect and mitigate input validation, injection risks, race conditions, and dependency vulnerabilities.
• DevOps & toolchain: Proficient with Docker (multi-stage builds), CI/CD pipelines (GitHub Actions, GitLab CI), and observability tooling (Prometheus, Grafana).
• Proof-of-work: Comfortable compiling and executing code in sandboxed environments to confirm functional compliance.
• Structured QA: Experienced with rubric-based scoring, checklist reviews, and ticketing/annotation tools (Jira, Asana).
• Communication: Excellent written English (B2+ CEFR) for clear, constructive feedback and mentoring.

Nice-to-have experience

These are not required but will help you succeed and stand out when applying.

• Exposure to LLM evaluation, RLHF pipelines, or prior AI/ML data-labeling projects.
• Familiarity with additional observability or sandboxing platforms beyond the core toolchain.

Who should apply

Apply if you are an experienced Go developer, QA engineer, or dedicated code reviewer who enjoys hands-on verification of code, mentoring annotators, and improving data quality for AI.

This role suits people who can work independently as contractors, follow rubric-based QA practices, and commit at least 20 hours per week.

• You are comfortable executing untrusted code in controlled sandboxes and reproducing bugs or edge cases.
• You can write concise, actionable feedback and correct annotator ratings to align with the rubric.
• You want remote, part-time contract work and can reliably meet the stated weekly hours.

How it works and how to apply

This is a remote, worldwide contractor role posted on OpenTrain. OpenTrain is a central job board for AI-training and data-labeling work — creating an account is free and applying typically takes only a few minutes.

If this role fits your background, create or sign into your OpenTrain account, submit your application, and highlight relevant Go projects, sandboxing experience, and examples of rubric-based review or mentoring.

• Contract, part-time engagement paid hourly at USD $24/hr.
• Work is remote and flexible but requires a minimum commitment of 20+ hours/week.
• Applications should demonstrate Go expertise, sandboxing/CI experience, and written English proficiency.