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Java programmer Jobs in Corpus Christi, TX
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Java programmer • corpus christi tx
Remote Senior Java Engineer - AI Trainer
SuperAnnotateCorpus Christi, Texas, USSENIOR APPLICATION PROGRAMMER ANALYST (GIS)
Tarrant CountyTarrant County, TX- Promoted
Programmer Analyst
TradeJobsWorkForce78411 Corpus Christi, TX, US- general dentist (from $ 50,000 to $ 225,000 year)
- associate dentist (from $ 145,600 to $ 209,000 year)
- dump truck (from $ 35,100 to $ 196,900 year)
- veterinarian (from $ 100,000 to $ 185,000 year)
- substitute teacher (from $ 23,400 to $ 180,619 year)
- engineering (from $ 54,438 to $ 180,000 year)
- process engineer (from $ 137,500 to $ 180,000 year)
- full stack developer (from $ 77,913 to $ 177,000 year)
- controls engineer (from $ 85,000 to $ 170,310 year)
- director of construction (from $ 124,323 to $ 169,487 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
SuperAnnotateCorpus Christi, 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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