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Java programmer Jobs in Miramar, FL
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Java programmer • miramar fl
Remote Senior Java Engineer - AI Trainer
SuperAnnotateNorth Miami, Florida, USAndroid Java Kotlin Mobile Developer
SherlockTalentHybrid South Florida- Promoted
Java / Backend Developer - Remote
SynergisticITPembroke Pines, FL, United States- cloud engineer (from $ 141,375 to $ 231,500 year)
- front end engineer (from $ 71,813 to $ 197,730 year)
- data scientist (from $ 91,250 to $ 182,000 year)
- data engineer (from $ 106,600 to $ 178,880 year)
- freelance (from $ 58,500 to $ 175,500 year)
- business development (from $ 48,750 to $ 175,000 year)
- business development director (from $ 88,518 to $ 175,000 year)
- medical director (from $ 135,000 to $ 172,500 year)
- solutions architect (from $ 157,500 to $ 170,250 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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Remote Senior Java Engineer - AI Trainer
SuperAnnotateNorth Miami, Florida, 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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