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Engineer • matane qc
Remote Kotlin Engineer - AI Trainer
SuperAnnotateMatane, Quebec, CAMarine Second Engineer
CN360Matane, La Matanie, CABridge Engineer / Ingénieur(e) – Conception en Ouvrages d’Art
McIntosh PerryQuebec, CAEngineering | Level 4 (CAD)
FX INNOVATIONRemote, QuebecMarine Second Engineer
CNMatane, Quebec, CAManufacturing Engineering Maintenance Manager
Harbour Industries CanadaQuebec, CA- Mississauga, ON (from $ 87,500 to $ 180,463 year)
- Goderich, ON (from $ 50,466 to $ 170,798 year)
- Yarmouth, NS (from $ 59,650 to $ 166,524 year)
- Listowel, ON (from $ 72,900 to $ 162,135 year)
- Aylmer, ON (from $ 72,804 to $ 160,773 year)
- Norfolk, ON (from $ 75,473 to $ 158,825 year)
- Squamish, BC (from $ 66,407 to $ 157,624 year)
- Carleton Place, ON (from $ 84,228 to $ 155,984 year)
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Remote Kotlin Engineer - AI Trainer
SuperAnnotateMatane, Quebec, CA- Full-time
- Remote
As a remote, hourly paid Kotlin Engineer, you will review AI-generated responses and generate high-quality Kotlin-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 information; craft expert-level explanations and model solutions that demonstrate correct approaches; and rate and compare multiple AI responses based on correctness and reasoning quality. T
his 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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