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Java programming Jobs in Abilene, TX
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Java programming • abilene tx
Remote Senior Java Engineer - AI Trainer
SuperAnnotateAbilene, Texas, USCommissioning Engineering Techs - PLC Troubleshooting • NO Programming
ActalentAbilene, TX, US- general dentist (from $ 20,000 to $ 240,000 year)
- mechanical engineer (from $ 105,000 to $ 200,000 year)
- project engineer (from $ 120,000 to $ 200,000 year)
- nurse practitioner (from $ 121,200 to $ 195,000 year)
- intern (from $ 20,000 to $ 183,300 year)
- pharmacist (from $ 114,985 to $ 173,264 year)
- energy (from $ 39,000 to $ 157,500 year)
- pacu rn (from $ 104,087 to $ 152,516 year)
- radiology (from $ 121,004 to $ 150,904 year)
- travel nursing (from $ 104,691 to $ 147,256 year)
The average salary range is between $ 90,000 and $ 162,565 year , with the average salary hovering around $ 120,938 year .
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Remote Senior Java Engineer - AI Trainer
SuperAnnotateAbilene, Texas, 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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