Rust AI Data Training Reviewer

About OpenTrain

OpenTrain is the leading platform for people building careers in AI training and data labeling. We connect experienced contributors with projects that need high-quality human feedback so you can build a durable freelance portfolio and grow your AI training career.

OpenTrain AI is the hiring and contracting organization for this role. We coordinate projects, contracts, and payments so you can focus on providing expert technical feedback.

Why AI Training Work Matters

AI systems learn from examples and human feedback. Reviewing model outputs, writing reference solutions, and rating explanations directly influence how models write code and justify technical decisions.

This kind of work is typically 100% remote, often flexible and part-time, and gives you direct influence over how state-of-the-art developer tools behave.

The Role

We are hiring a Rust AI Data Training Reviewer to examine AI-generated Rust code and explanations, create model solutions when needed, and judge the quality, safety, and prompt adherence of model reasoning. The role focuses on finding correctness, safety, and idiomatic style issues and providing clear, structured feedback that improves model outputs.

• Position type: Remote contractor, part-time (20+ hours/week).
• Pay: $60 USD per hour, paid to contractors by OpenTrain AI.
• Work involves reviewing code, writing solutions, and rating/evaluating model responses (RLHF, evaluation, text generation tasks).

What You'll Do

• Review AI-generated Rust code and explanations for correctness and idiomatic style.
• Write high-quality Rust reference solutions and step-by-step technical explanations when required.
• Evaluate reasoning quality, safety, stepwise problem solving, and adherence to prompts.
• Identify ownership, borrowing, lifetime, concurrency, and algorithmic-logic issues.
• Compare and rate multiple model responses for accuracy, clarity, and safety.
• Provide detailed, actionable feedback to help improve AI-generated technical content.

Requirements

You must meet the core qualifications below to be considered. All requirements come from the role description and will be used to evaluate applicants.

• 1–2+ years professional Rust development experience in backend, CLI, or systems programming.
• Strong, demonstrable understanding of Rust ownership, borrowing, lifetimes, and memory safety.
• Experience with backend services, command-line tools, or systems programming in Rust.
• Ability to evaluate safe, idiomatic Rust: traits, generics, pattern matching, and error handling.
• Excellent English writing skills with precise, structured technical explanations.
• Bachelor’s degree in Computer Science or a closely related technical field.
• Availability for 20+ hours per week as a contractor (part-time).
• Authorized to work as a contractor from one of these countries: BD, BT, BR, KH, DE, IN, ID, MY, NP, PK, SG, LK, TH, PH, US, TL, VN.
• Familiarity with async Rust patterns is required; experience with Tokio, Actix, Serde is strongly preferred.
• Experience reviewing AI-generated or production Rust code for correctness and safety.
• Experience using LLMs or coding assistants with disciplined validation is preferred.

Helpful Background

• Competitive programming experience or strong algorithmic problem solving.
• Contributions to Rust open-source projects or public code samples.
• Demonstrated attention to performance, concurrency, and correctness in production code.

How to Apply and What to Expect

Create a free OpenTrain account to apply and build a profile that records your AI training work. OpenTrain centralizes opportunities and helps you present prior work as proof-of-skill for future contracts.

If selected, you will contract with OpenTrain AI and be paid at the advertised hourly rate. This is a remote contractor role; scheduling is typically flexible but requires a minimum commitment of 20 hours per week.

• Language requirement: English (written).
• Labeling/data type: computer code (programming); tasks include question-answering, evaluation/rating, RLHF, and text generation evaluation.