Key Responsibilities:

• Develop AI Training Content: Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects.
• Optimize AI Performance: Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance.
• Ensure Model Integrity: Test AI models for potential inaccuracies or biases, validating their reliability across use cases.

Requirements:

• 1–2+ years of professional Rust development experience in backend, CLI, or systems-focused projects.
• Strong understanding of Rust’s ownership, borrowing, and lifetime model, 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 appropriate use of traits, generics, pattern matching, and 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.

Key Responsibilities:

• Develop AI Training Content: Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects.
• Optimize AI Performance: Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance.
• Ensure Model Integrity: Test AI models for potential inaccuracies or biases, validating their reliability across use cases.

Requirements:

• 1–2+ years of professional Rust development experience in backend, CLI, or systems-focused projects.
• Strong understanding of Rust’s ownership, borrowing, and lifetime model, 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 appropriate use of traits, generics, pattern matching, and 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.