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Python programming Jobs in Victorville, CA
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Python programming • victorville ca
Remote Senior Python Engineer - AI Trainer
SuperAnnotateVictorville, California, US- psychiatrist (from $ 200,000 to $ 240,000 year)
- hospital (from $ 50,000 to $ 223,000 year)
- assistant superintendent (from $ 185,620 to $ 218,026 year)
- architect (from $ 60,970 to $ 217,948 year)
- project manager (from $ 61,425 to $ 200,000 year)
- city (from $ 47,561 to $ 191,502 year)
- dentist (from $ 96,798 to $ 188,528 year)
- clinical pharmacist (from $ 148,704 to $ 187,200 year)
- software engineer (from $ 105,000 to $ 182,500 year)
The average salary range is between $ 95,000 and $ 145,000 year , with the average salary hovering around $ 109,600 year .
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Remote Senior Python Engineer - AI Trainer
SuperAnnotateVictorville, California, US- Full-time
- Remote
As a Senior Python Engineer, you will work remotely on an hourly paid basis to review AI-generated Python solutions and technical explanations, as well as generate high-quality reference content that demonstrates strong software engineering practices. You will assess solutions for correctness, code quality, performance, and adherence to the prompt; identify errors in logic, architecture, or methodology; fact-check technical information; craft clear, step-by-step explanations and exemplary solutions; and rate and compare multiple AI responses based on their reasoning quality and implementation soundness.
This is a fully remote, hourly paid contractor role with SME Careers, a fast-growing AI data services company and subsidiary of SuperAnnotate that provides AI training data to many of the world’s largest AI companies and foundation model labs, where your Python expertise will directly help 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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