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Electronics engineer Jobs in Quesnel, BC
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Electronics engineer • quesnel bc
Swift Engineer
SuperAnnotateQuesnel, British Columbia, CASenior Machine Learning Engineer
InstacartCanada (AB, BC, ON, NS ONLY)Maintenance Power Engineers - 3rd Class
Sofina FoodsBritish Columbia, CanadaSr Software Engineer
SUSEAll, British Columbia, CanadaPrincipal Software Engineer
ServiceTitanCanada British ColumbiaSenior Hydrologist / Water Resources Engineer
StantecQuesnel, BC, CASenior Cloud Data Engineer
Providence Health CareHybridVancouver, British Columbia, 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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Swift Engineer
SuperAnnotateQuesnel, British Columbia, CA- Full-time
- Remote
As a remote, hourly paid Swift Engineer, you will review AI-generated responses and generate high-quality Swift and iOS-focused content, evaluating the reasoning quality and step-by-step problem-solving behind each solution. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify errors in methodology or conceptual understanding; fact-check technical details; write expert-level explanations and model solutions that demonstrate correct approaches in Swift and iOS; 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, 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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