Remote Backend Engineer for AI Training — Secure

YO AI Labs; New York (NY); Remote; USD 69,000 - 96,000; Part time

Job summary

YO AI Labs is seeking experienced Backend Software Engineers to support AI training through challenging coding tasks and reliable evaluation systems. You will develop and review backend features, APIs, and scalable services while focusing on performance, security, and code quality.

Role is a contractor position with about 15 hours per week. You will work remotely with flexible scheduling, tackling debugging, refactoring, and secure coding tasks that contribute to robust AI training

Qualifications

• Strong backend development experience with Python, Java, Rust, C++, TypeScript, or similar languages.
• Solid understanding of algorithms, data structures, and software engineering principles.
• Experience with debugging, testing, performance optimization, and code reviews.
• Experience with cybersecurity, pentesting, vulnerability assessment, or security audits is a plus.

Responsibilities

• Develop and review backend features, APIs, and scalable services.
• Identify and resolve bugs, performance issues, and code quality problems.
• Refactor and optimize existing codebases.
• Create challenging coding tasks and deterministic evaluation criteria.
• Apply secure coding practices and conduct security-focused reviews.
• Provide clear technical feedback and documentation.

Skills

Python 3

Java

Rust

C++

TypeScript

Algorithms & Data Structures

Bug Fixing

Feature Implementation

Codebase Refactoring

Performance Optimization

Automated Testing

Pentesting

Security Auditing

Cybersecurity

Job description

YO AI Labs is seeking experienced Backend Software Engineers to support AI training through challenging coding tasks and reliable evaluation systems. You will develop and review backend features, APIs, and scalable services while focusing on performance, security, and code quality.

Role is a contractor position with about 15 hours per week. You will work remotely with flexible scheduling, tackling debugging, refactoring, and secure coding tasks that contribute to robust AI training