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Server • cornwall on
Remote C# Software Engineer - AI Trainer
SuperAnnotateCornwall, Ontario, CAJPC - 1322 - Business Systems Analyst (BSA)
ITS GlobalOntarioIT Security Admin / Core Technology
Procor LimitedRemote, OntarioServer
Chartwell Retirement ResidencesCornwall, ON, CAServer
Boston Pizza International IncCornwall, ON, CAL2 Deskside Support Engineer
Tata Consultancy ServicesOntario, CAServer
The Party Staff IncOntario, CASr. SharePoint Developer
Medavie Blue CrossON, CANight Crew Member
McDonald'sCornwall, Ontario, CanadaPest Technician - We'll Train! (Base Salary, Commission & Bonus included)
Abell Pest ControlCornwall, ON K6H 1B6, CAN- Sainte-Therese, QC (from $ 33,272 to $ 168,539 year)
- Markham, ON (from $ 30,225 to $ 153,269 year)
- Salmon Arm, BC (from $ 30,518 to $ 140,031 year)
- Brampton, ON (from $ 33,638 to $ 130,000 year)
- Montreal, QC (from $ 35,137 to $ 124,279 year)
- Montreal-Ouest, QC (from $ 35,097 to $ 124,123 year)
- Montreal-Est, QC (from $ 35,027 to $ 124,029 year)
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Remote C# Software Engineer - AI Trainer
SuperAnnotateCornwall, Ontario, CA- Full-time
- Remote
This is an hourly-paid, fully remote contractor role where you will review AI-generated responses and / or generate C# / .NET engineering content, evaluating reasoning quality and step-by-step problem-solving. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify errors in methodology or conceptual understanding; fact-check technical claims; and rate / compare multiple responses based on correctness and reasoning quality. You will also produce high-quality explanations and model solutions that demonstrate correct methods and clear communication. 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—your work directly helps 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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