Open AI training and model evaluation roles that call for Code Quality & Review expertise, gathered from 7 platforms. Part of Software Engineering.
Pay figures cover the 122 open jobs that publish an hourly rate in USD. They are published rates, not a guarantee of income. Last checked on October 8, 2026.
This remote contract role involves running code written by AI, checking whether it behaves as intended, and recording bugs and quality issues in structured reports. It suits people who can read and run simple programs in at least one language and think logically, without needing a formal QA or computer science background.
This is a remote hourly contract for a senior Rust engineer who will design and maintain high-performance data pipelines, annotation tooling, and evaluation systems used to train AI models. The work is production-focused, involves backend and tooling services, and suits engineers who can work independently with research and data teams.
This is a remote hourly contract for senior systems engineers who will build and tune the C++ infrastructure behind AI data pipelines, annotation tools and model evaluation. The work centers on performance, reliability and production fixes, carried out alongside research and engineering teams. It suits experienced C++ developers with a systems background who want to work on the infrastructure used to train and ship AI models.
This remote contract role asks senior TypeScript developers to review AI-generated code for type safety, scalability and modern practices. The work centers on writing structured feedback that helps AI models understand architectural choices and type logic. It is aimed at experienced developers who can work independently on flexible hourly commitments.
This contract role asks TypeScript developers to review and improve AI-generated code so it is type-safe, idiomatic, scalable and ready for production. It is aimed at senior developers with deep TypeScript knowledge who can clearly explain why a piece of code is well designed. No prior AI background is required.
As an Application Security Engineer, you will evaluate how AI models reason about secure design and identify security vulnerabilities they miss, including architectural flaws, unsafe deserialization, and overly permissive access controls. You will threat-model systems, conduct security code reviews, and write clear guidance on secure design and vulnerability fixes.
Backend engineers will evaluate how AI models reason about system design, data modeling, and API contracts, identifying failures like race conditions and N+1 queries that only surface under real load. The role involves stress-testing model-generated backend code and writing correct solutions when models fall short, with explicit attention to scaling and consistency trade-offs.
This role involves evaluating AI models' ability to generate secure code by identifying vulnerabilities, testing their security reasoning, and writing corrections when they fail. It suits security engineers and cybersecurity professionals who can spot weaknesses in authentication, cryptography, input handling, and secret management that automated tools miss.
Evaluate how AI models handle DevOps tasks such as CI/CD pipelines, infrastructure-as-code, and cloud operations. Identify failures in automation, security configurations, and deployment processes, then write correct solutions that a platform engineer would trust.
Evaluate and stress-test user interfaces built by AI models to identify frontend failures in components, state management, accessibility, and rendering. Write correct implementations when models fall short, providing the training signal through clear technical explanations of what works and what breaks.
This role involves evaluating how AI models handle incident response tasks including detection, triage, and forensics. You will identify flaws in the model's reasoning, catch critical mistakes that would compromise real security incidents, and write correct analysis based on actual incident response practices.
You will evaluate AI-generated code by running models on real engineering tasks, analyzing their output against production standards, and stress-testing them to find failures. This role is ideal for experienced software engineers who want to contribute to AI model improvement through rigorous code review and red-teaming.
Research role focused on evaluating code generation by LLMs: designing evaluation frameworks and criteria.
Referral link to micro1's job list: search for this role there. Open this exact job
This contract role centers on testing 2D design, animation, illustration and other creative applications through realistic designer and animator workflows. The work is to find bugs and usability problems, document them clearly, and help improve how AI systems are evaluated. It suits QA professionals who also know creative software well.
Posted October 7, 2026
Referral link to micro1's job list: search for this role there. Open this exact job
This contract role asks an experienced mobile engineer to design realistic coding challenges that test how well AI models handle mobile software problems such as bug fixing, feature building, refactoring and performance work. For each challenge the expert builds a reproducible environment, writes verifiers that accept varied correct solutions and reject shortcuts, and provides a reference solution. It suits developers with deep hands-on experience in React Native, Flutter, SwiftUI, UIKit, Jetpack Compose or Android Views.
Posted October 7, 2026
Referral link to micro1's job list: search for this role there. Open this exact job
This is a paid evaluation role for database engineers who will design realistic tasks that test how well AI agents handle database work. Each task is a self-contained problem with a reproducible environment, a working reference solution, tests, and grading criteria that separate robust engineering from code that only looks correct. It is aimed at experts with deep database-engine internals experience, not at DBA, SQL analytics, or ETL-only profiles.
Posted October 6, 2026
You will contribute to training next-generation AI models by creating realistic coding tasks and implementing deterministic verifiers. This flexible contracting role is aimed at experienced backend engineers capable of generating relevant technical challenges and automatically evaluating solutions.
Posted October 6, 2026
Referral link to micro1's job list: search for this role there. Open this exact job
Evaluation of AI model outputs against correctness, maintainability, security, and production readiness criteria, accessible to early-to-mid career professionals.
Evaluation and comparison of AI model solutions on realistic software engineering tasks: debugging, cross-repository logic tracing, feature implementation, code review, architecture decisions.
Deep expertise in network engineering, legacy/enterprise systems and advanced programming languages (CUDA, C++, Rust, MLOps, COBOL, ABAP, Scala, Kotlin, OCaml).
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FAQ
127 Code Quality & Review AI training jobs are open on SideHustler today. 5 were posted in the last 7 days. Listings are rechecked against the official postings: the latest check on this list was on October 8, 2026.
Among the 122 open roles that publish an hourly rate in USD, pay runs from $20 to $350 per hour, with a median of $75. These are the rates the platforms publish, not a guarantee of income or hours.
Alignerr (65), Mercor (26), micro1 (23), DataAnnotation (7), Terac (3), Vetto (2) and xAI (1). You apply on the platform itself, which handles screening, contracts and payment.
The most requested areas of expertise on these listings are Code Quality & Review, AI Evaluation, System Design, Python, Backend Development. Each listing states its own requirements.
Apply now opens the official posting on the platform, where you complete the application. You need no account on SideHustler. To see which roles fit your background first, add your resume and every open job is scored against your profile.
