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Controller • cranbrook bc
Ruby Engineer
SuperAnnotateCranbrook, British Columbia, CA- Sault Ste. Marie, ON (from $ 92,839 to $ 207,252 year)
- Belleville, ON (from $ 100,000 to $ 206,455 year)
- Langley, BC (from $ 105,000 to $ 197,580 year)
- Pictou, NS (from $ 78,750 to $ 197,100 year)
- St. John's, NL (from $ 80,000 to $ 196,310 year)
- Laval, QC (from $ 87,500 to $ 196,234 year)
- Leamington, ON (from $ 70,446 to $ 196,113 year)
- Cole Harbour, NS (from $ 45,000 to $ 196,005 year)
- Dollard-Des Ormeaux, QC (from $ 95,000 to $ 195,988 year)
- Levis, QC (from $ 80,000 to $ 195,937 year)
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Ruby Engineer
SuperAnnotateCranbrook, British Columbia, CA- Full-time
- Remote
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.
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.
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