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Electronics engineer • swift current sk
Remote Ruby Engineer - AI Trainer
SuperAnnotateSwift Current, Saskatchewan, CAMaintenance Power Engineers - 3rd Class
Sofina FoodsSaskatchewan, CanadaSenior Engineer, Plant Engineering Services North (Electrical)
SaskPowerSWIFT CURRENT, SK, CA- Chatham-Kent, ON (from $ 138,675 to $ 197,708 year)
- Oakville, ON (from $ 75,231 to $ 193,246 year)
- Sault Ste. Marie, ON (from $ 112,250 to $ 176,956 year)
- Chilliwack, BC (from $ 172,069 to $ 174,376 year)
- Conception Bay South, NL (from $ 126,773 to $ 174,376 year)
- Thunder Bay, ON (from $ 98,386 to $ 156,935 year)
- Glace Bay, NS (from $ 98,386 to $ 156,935 year)
- Newmarket, ON (from $ 75,000 to $ 153,805 year)
- The Pas, MB (from $ 54,883 to $ 153,651 year)
- Victoria, BC (from $ 83,216 to $ 152,764 year)
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Remote Ruby Engineer - AI Trainer
SuperAnnotateSwift Current, Saskatchewan, 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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