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Remote Graphic designer Jobs in Antioch ca
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Graphic designer • antioch ca
Remote Graphic Designer - AI Trainer
SuperAnnotateOakley, California, USSenior Presentation Designer (PPT & Keynote)
Horizontal TalentRemote, California, USMultimedia Designer
Uniting HoldingBrentwood, CA, United StatesWeb Designer-UX
Loma Linda Unv Shared ServicesRemote, CaliforniaThe average salary range is between $ 40,950 and $ 80,430 year , with the average salary hovering around $ 66,713 year .
- veterinarian (from $ 60,000 to $ 215,000 year)
- engineering (from $ 110,000 to $ 204,000 year)
- modeling (from $ 172,250 to $ 200,500 year)
- machine learning engineer (from $ 66,938 to $ 200,000 year)
- psychiatrist (from $ 125,000 to $ 200,000 year)
- software engineer (from $ 143,000 to $ 200,000 year)
- clinical director (from $ 117,500 to $ 198,633 year)
- design engineer (from $ 71,250 to $ 198,300 year)
- machine learning (from $ 97,500 to $ 198,000 year)
The average salary range is between $ 39,000 and $ 77,883 year , with the average salary hovering around $ 50,974 year .
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Remote Graphic Designer - AI Trainer
SuperAnnotateOakley, California, US- Full-time
- Remote
This is a remote, hourly-paid contractor role where you will review AI-generated responses and / or generate high-quality creative content, evaluating reasoning quality and step-by-step problem-solving. You’ll will create model CoTs to train an LLM to analyze image prompts more effectively. SME Careers is a fast-growing AI Data Services company and a subsidiary of SuperAnnotate, providing AI training data for many of the world’s largest AI companies and foundation-model AI labs. Your work directly helps improve the world’s premier AI models by bringing strong creative judgment and rigorous evaluation to every task.
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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