Rust Developer

Responsibilities

• Develop AI training content: Craft comprehensive prompts across diverse topics and create model responses to guide AI learning, ensuring broad subject coverage.
• Optimize AI performance: Assess and rank AI responses to improve model accuracy, fluency, and contextual relevance.
• Ensure model integrity: Test AI models for inaccuracies or biases, validating reliability across use cases.

Requirements

• 1–2+ years of professional Rust development experience in backend, CLI, or systems-focused projects.
• Strong understanding of Rust ownership, borrowing, and lifetimes, with the ability to reason clearly about aliasing and data races.
• Solid software engineering experience in at least one of backend services, command-line tools, or systems programming using Rust.
• Ability to evaluate safe, idiomatic Rust code, including traits, generics, pattern matching, and robust error handling.
• Significant experience using LLMs or AI coding assistants while programming, combined with a disciplined approach to validating their output.
• Excellent English writing skills, capable of producing precise, structured, and pedagogical technical explanations.
• Minimum Bachelor's degree in Computer Science or a closely related technical field.
• Previous experience with AI data training, code review at scale, or evaluation of AI-generated technical content is strongly preferred; minimum C1 English proficiency and an extremely detail-oriented working style are required.
• Highly preferred: experience with Tokio, Actix, Serde, and async Rust patterns in production or advanced side projects.
• Preferred: competitive programming experience, contributions to Rust open-source ecosystems, and demonstrated ability to reason about performance, concurrency, and correctness in Rust code.

Technologies

• Rust
• Tokio
• Actix
• Serde

Role Description

As an hourly paid, fully remote Rust Engineer for AI Data Training, you will review AI-generated Rust code and explanations or generate your own, evaluate the reasoning quality and step-by-step problem-solving, and provide expert feedback that helps models produce answers that are accurate, logical, and clearly explained. You will assess solutions for correctness, safety, and adherence to the prompt; identify errors in ownership, borrowing, lifetimes, or algorithmic reasoning.