Senior Docker Code Reviewer

About OpenTrain AI

OpenTrain AI is the #1 platform for finding and building careers in AI training and data labeling. We connect skilled contributors with hands-on work that shapes how modern AI systems behave. OpenTrain AI is the hiring and contracting organization for this role.

• Work remotely for a leader in the AI training industry.
• Flexible, part-time contractor opportunities that fit around other commitments.

About AI Training Work

AI training (data labeling/annotation) is the human side of building intelligent systems: real people prepare and review examples—code, text, images, and more—that models learn from. This project focuses on evaluating AI-generated Dockerfiles and container-related snippets so future models generate safer, more reliable infrastructure code.

These roles are ideal if you want flexible, impactful work where your reviews directly influence how next-generation AI handles containers and deployments.

• 100% remote work with flexible scheduling.
• Entry to senior opportunities exist; many projects need domain fluency rather than formal certifications.

The Role

You will act as a senior Docker reviewer—part DevOps engineer, part security auditor—validating annotator ratings of AI-generated Dockerfiles, Docker Compose and container-orchestration snippets. Your reviews protect the container data used to train models by ensuring correctness, security, and adherence to best practices.

• Title: Senior Docker Code Reviewer (contractor, part-time).
• Commitment: 20+ hours per week.
• Pay: $24 per hour (PAY_PER_HOUR, USD).
• Work location: Remote / worldwide.

What you'll do

For each submission you will build and run the image in an isolated sandbox, verify functional behavior against the prompt, assess security and best-practice compliance, and confirm the annotator's score matches the project rubric. When issues are found you will flag incorrect ratings and provide concise, actionable remediation notes.

• Reproduce builds in sandboxed VMs or rootless environments to confirm functional compliance.
• Verify adherence to prompts and functional requirements.
• Check for multi-stage builds, minimal base images, non-root users, and efficient layer caching.
• Spot privilege escalation, hard-coded secrets, outdated base images, and vulnerable packages.
• Use scanning tools (Trivy, Grype, Dockle) and registry checks as part of evaluation.
• Provide succinct remediation guidance and confirm annotator corrections.

Requirements

This role expects strong, hands-on container expertise and experience conducting technical code reviews. All proven requirements below come from the role specification and are essential to perform the work accurately.

• Experience: 7+ years in DevOps, SRE, or container-focused engineering with regular code-review duties.
• Docker mastery: deep knowledge of Dockerfile syntax, multi-stage builds, image slimming, BuildKit and Docker Compose workflows.
• Security & compliance: expert at spotting privilege escalation, hard-coded secrets, vulnerable packages, outdated base images, and root-user pitfalls.
• CI/CD & toolchain: proficiency with GitHub Actions/GitLab CI, scanning tools (Trivy, Grype, Dockle), and registry management.
• Testing & debugging: ability to reproduce build failures, analyze layer diffs, and tune builds for cache and context size.
• Proof-of-work validation: comfortable running containers in sandboxed VMs or rootless modes.
• Structured QA: experience with rubric-based scoring, ticketing systems, and annotation workflows.
• Communication: strong written English (B2+ CEFR) to deliver clear, actionable feedback.

Nice to have

These preferred skills are not required but will help you stand out and be more effective on this project.

• Familiarity with Helm, Kustomize, and container runtime nuances (containerd, CRI-O).
• Experience mentoring engineers on container best practices.
• Exposure to LLM evaluation, RLHF pipelines, or AI/ML data-labeling projects.

How it works / What to expect

You will be engaged as a contractor through OpenTrain AI. Tasks are supplied as annotation reviews tied to a quality rubric; you will accept batches, complete sandboxed validation, and submit your review and remediation notes. The project requires adherence to a strict review checklist and consistent scoring.

• Employment type: Contractor, part-time.
• Schedule: flexible; project expects 20+ hours/week availability.
• Compensation: $24/hour, paid per hour according to recorded time and project rules.
• Quality: reviewers must follow the provided rubric and record brief, actionable remediation notes when flagging issues.

Who should apply

Apply if you are a practiced DevOps or SRE professional who enjoys code review, container security, and teaching others via concise feedback. This is a great role for someone who wants flexible remote work and to directly influence how AI learns to generate safe, efficient container code.

• You enjoy hands-on debugging and reproducing builds in isolated environments.
• You can write clear remediation notes and uphold a structured QA rubric.
• You want part-time, remote contractor work that impacts AI training data quality.