Remote Research Engineer: Code Gen & AI Task Eval

YO AI Labs; Bogotá ciudad; A distancia; COP 55.255.000 - 147.346.000; Jornada completa

Descripción de la vacante

YO AI Labs is seeking experienced Research Engineers for a remote, contractor role focused on code generation, software engineering, and AI model evaluation. You will work across Python, Java, Rust, C++, Go, or TypeScript to develop, review, and evaluate real-world coding tasks that train next-generation AI systems.

Responsibilities include analyzing codebases, implementing new features, refactoring for performance, developing coding tasks, and annotating results to support model training.

Formación

• Strong abilities in competitive programming and algorithms.
• Experience debugging, feature implementation, and refactoring.
• Proficiency in at least one language from Python/Java/Rust/C++/Go/TS.
• Open-source contributions or collaborative projects are a plus.
• Excellent analytical, problem solving, and communication skills.

Responsabilidades

• Analyze, debug, and resolve issues across codebases.
• Implement features for code generation workflows.
• Refactor and optimize code for performance and maintainability.
• Develop and review coding tasks for AI model evaluation.
• Provide feedback and annotations to support training.
• Collaborate with contributors on software quality.
• Document technical decisions and best practices.

Conocimientos

Competitive programming

Algorithms & data structures

Programming languages

Code debugging

Open-source contributions

Problem solving

Communication skills

Detail oriented

Remote work ability

Herramientas

Git

Unit testing

Code review

Descripción del empleo

YO AI Labs is seeking experienced Research Engineers for a remote, contractor role focused on code generation, software engineering, and AI model evaluation. You will work across Python, Java, Rust, C++, Go, or TypeScript to develop, review, and evaluate real-world coding tasks that train next-generation AI systems.

Responsibilities include analyzing codebases, implementing new features, refactoring for performance, developing coding tasks, and annotating results to support model training.