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Java programmer • springfield il
Senior Java Engineer
SuperAnnotateSpringfield, Illinois, US- live in nanny (from $ 24,375 to $ 390,000 year)
- software architect (from $ 110,000 to $ 245,700 year)
- senior software engineer (from $ 120,442 to $ 234,900 year)
- business operations manager (from $ 89,244 to $ 213,719 year)
- process engineer (from $ 72,500 to $ 207,750 year)
- technical director (from $ 65,750 to $ 205,643 year)
- computer engineer (from $ 66,480 to $ 202,500 year)
- engineering director (from $ 143,810 to $ 202,500 year)
- data architect (from $ 140,400 to $ 201,282 year)
- pediatric dentist (from $ 22,500 to $ 200,000 year)
The average salary range is between $ 87,919 and $ 136,500 year , with the average salary hovering around $ 106,479 year .
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Senior Java Engineer
SuperAnnotateSpringfield, Illinois, US- Full-time
- Remote
As a Senior Java Engineer, you will work remotely on an hourly paid basis to review AI-generated Java code, architectural solutions, and technical explanations, as well as generate high-quality reference implementations and reasoning steps. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify errors in logic, performance, or design; fact-check technical information; write high-quality explanations and model solutions that demonstrate correct methods; and rate and compare multiple AI responses based on correctness and reasoning quality.
This fully remote, hourly paid contractor role is 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 Java 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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