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Junior java developer Jobs in Brownsville, TX
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Junior java developer • brownsville tx
Senior Java Engineer
SuperAnnotateBrownsville, Texas, US- Promoted
Remote Side Hustle Developer
Finance BuzzOlmito, Texas, USData Entry Operator | Junior (Remote)
Only Data Entry ClerkBrownsville, TX, United States- software engineer (from $ 126,789 to $ 190,000 year)
- crane operator (from $ 59,670 to $ 187,200 year)
- server (from $ 24,863 to $ 182,000 year)
- substitute teacher (from $ 170,625 to $ 180,375 year)
- data engineer (from $ 116,181 to $ 170,000 year)
- data scientist (from $ 59,280 to $ 164,000 year)
- nurse practitioner (from $ 116,500 to $ 158,655 year)
- network engineer (from $ 101,400 to $ 157,500 year)
The average salary range is between $ 67,419 and $ 107,250 year , with the average salary hovering around $ 80,000 year .
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Senior Java Engineer
SuperAnnotateBrownsville, 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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