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Cloud architect Jobs in Cornwall, ON
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Cloud architect • cornwall on
Remote Bash / PowerShell Engineer - AI Trainer
SuperAnnotateCornwall, Ontario, CAIT Security Admin / Core Technology
Procor LimitedRemote, OntarioSenior Software Engineer, Ads Contextual Intelligence
redditRemote, Ontario, CanadaSr. SharePoint Developer
Medavie Blue CrossON, CAPrincipal Software Engineer
ServiceTitanCanada OntarioJPC - 1425 - Lead Web Backend Developer(NodeJS)
ITS GlobalOntario- St. Catharines, ON (from $ 155,001 to $ 266,908 year)
- St. Thomas, ON (from $ 155,001 to $ 266,908 year)
- St. Albert, AB (from $ 133,160 to $ 257,356 year)
- Red Deer, AB (from $ 104,736 to $ 228,700 year)
- Calgary, AB (from $ 124,405 to $ 228,700 year)
- Niagara Falls, ON (from $ 124,582 to $ 192,095 year)
- Markham, ON (from $ 92,830 to $ 175,500 year)
- Saint-Laurent, QC (from $ 121,929 to $ 174,765 year)
- Cote-Saint-Luc, QC (from $ 121,929 to $ 174,765 year)
- Halifax, NS (from $ 92,830 to $ 173,165 year)
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Remote Bash / PowerShell Engineer - AI Trainer
SuperAnnotateCornwall, Ontario, CA- Full-time
- Remote
As a remote, hourly paid Bash / PowerShell Engineer, you will review AI-generated responses and generate high-quality automation-focused content, evaluating the reasoning quality and step-by-step problem-solving behind scripts and troubleshooting workflows. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify errors in logic, safety, or portability; fact-check technical details; write expert-level explanations and model solutions that demonstrate correct scripting patterns; and rate and compare multiple AI responses based on correctness and reasoning quality. This contract 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, directly helping to improve the world’s premier AI models.
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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