Ruby Engineer - AI Training (Part Time, Freelance, Remote, 20+ openings)

Ruby Developer; New Jersey; Remote; USD 80,000 - 120,000; Full time

Job summary

SME Careers is seeking a remote Ruby Engineer to review AI-generated Ruby and Rails code, ensuring its accuracy and clarity. Ideal candidates will have 1-2+ years of programming experience, strong knowledge of Ruby on Rails, and excellent English writing skills. Responsibilities include developing AI training content and optimizing AI performance by testing and validating model integrity. This role provides the flexibility of working remotely while directly impacting AI model development.

Qualifications

• 1-2+ years of professional Ruby programming experience in production environments.
• Strong understanding of Ruby on Rails, MVC architecture, and idiomatic Ruby patterns.
• Hands-on software engineering experience in maintaining Ruby or Rails applications.
• Ability to evaluate readability and logical correctness in Ruby and Rails code.
• Minimum C1 English proficiency and extremely detail-oriented working style required.

Responsibilities

• Create detailed prompts and responses for AI learning.
• Evaluate and rank AI responses to enhance model accuracy.
• Test AI models for potential inaccuracies or biases.

Skills

Professional Ruby programming experience

Understanding of Ruby on Rails

Ability to evaluate code readability

Excellent English writing skills

Education

Bachelor's degree in Computer Science

Tools

Ruby on Rails

RSpec

Job description

Job Description

Compensation is competitive and varies based on location, education level, and prior experience.

Role Description

As an hourly paid, fully remote Ruby Engineer for AI Data Training, you will review AI-generated Ruby and Rails code or generate your own solutions, 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 readability, maintainability, and correctness; identify errors in MVC structure, domain modeling, or control flow; fact‑check information; write high‑quality explanations and model solutions that demonstrate idiomatic Ruby patterns; and rate and compare multiple AI responses based on correctness and reasoning quality. This role is with SME Careers, a fast‑growing AI Data Services company and subsidiary of SuperAnnotate that provides AI training data for many of the world’s largest AI companies and foundation model labs, and your work will directly help improve the world’s premier AI models while giving you the flexibility of impactful, detail‑oriented remote contract work.

Your Profile

• 1–2+ years of professional Ruby programming experience in production environments.
• Strong understanding of Ruby on Rails, MVC architecture, and idiomatic Ruby patterns for structuring application code.
• Hands‑on software engineering experience building and maintaining Ruby or Rails applications, with exposure to real‑world production constraints.
• Ability to evaluate readability, maintainability, and logical correctness in Ruby and Rails code, including model, controller, and service‑layer design.
• Significant experience using LLMs or AI coding assistants while programming, combined with a disciplined approach to validating and reviewing their output.
• Excellent English writing skills, capable of producing clear, structured, and pedagogical technical explanations and code reviews.
• Minimum Bachelor’s degree in Computer Science or a closely related technical field.
• Previous experience with AI data training, large‑scale code review, 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 frameworks and tools such as Ruby on Rails, Sinatra, and RSpec in real projects.
• Preferred: merged PRs in Ruby open‑source projects, experience with metaprogramming or test‑heavy systems, and competitive programming exposure.

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.