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Sql developer Jobs in Norfolk, VA
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Sql developer • norfolk va
Remote Senior SQL Engineer - AI Trainer
SuperAnnotateChesapeake, Virginia, USSoftware Developer
SsgNorfolk, Virginia, United States- Promoted
Intel / OPFOR Developer
PrevailanceNorfolk, VA, USApplications Developer
QVineNorther Virginia VA.Net Developer
GDIT(VAHOME), Office, Home, VA, USA- Promoted
SharePoint Developer
CSA Global LLCPortsmouth, VA, USMaintenance Developer
ITA International, LLCPortsmouth, VA, US- Promoted
Database Administrator / Software Developer
Unified Business Technologies IncNorfolk, VA, US- Promoted
Full Stack Developer (N)
SimIS Inc.Norfolk, VA, USM365 Developer
CACI International IncNorfolk, VA, US- Promoted
SharePoint / PowerApps Developer
Interactive Process Technology LLCPortsmouth, VA, USSQL Developer
VirtualVocationsPortsmouth, Virginia, United States- Promoted
Full Stack Developer
Connect Talent SolutionsNorfolk, VA, USLead Developer
Old Dominion UniversityNorfolk, VA- Promoted
SAP Data Services Developer
Imagine One Technology & Management LtdNorfolk, VA, US- Promoted
Microsoft SQL Server (MSSQL) Database Administrator (On-Site)
Oxley Enterprises®, Inc.Norfolk, VA, US- Promoted
ORACLE DATABASE DEVELOPER
VSolvitChesapeake, VA, US- Promoted
Integrations Developer-Remote Opportunity
YELLOW DOG SOFTWARE LLCNorfolk, VA, USFull Stack Developer (N)
SimisNorfolk, Virginia, United StatesThe average salary range is between $ 87,500 and $ 150,000 year , with the average salary hovering around $ 101,400 year .
- construction foreman (from $ 58,000 to $ 262,412 year)
- operations engineer (from $ 97,293 to $ 234,900 year)
- mental health nurse (from $ 135,000 to $ 232,120 year)
- software architect (from $ 145,000 to $ 225,000 year)
- principal software engineer (from $ 126,275 to $ 211,855 year)
- engineering director (from $ 177,500 to $ 210,000 year)
- software engineering manager (from $ 151,175 to $ 210,000 year)
- it director (from $ 19,500 to $ 204,263 year)
- chief estimator (from $ 70,200 to $ 200,000 year)
- general dentist (from $ 100,000 to $ 200,000 year)
- Austin, TX (from $ 96,769 to $ 150,800 year)
- Norfolk, VA (from $ 87,500 to $ 150,000 year)
- San Francisco, CA (from $ 95,597 to $ 146,523 year)
- Houston, TX (from $ 95,256 to $ 145,600 year)
- Seattle, WA (from $ 97,500 to $ 145,000 year)
- New York, NY (from $ 100,000 to $ 140,786 year)
- Los Angeles, CA (from $ 97,500 to $ 140,000 year)
- Denver, CO (from $ 84,600 to $ 136,500 year)
- Atlanta, GA (from $ 91,450 to $ 136,305 year)
- Dallas, TX (from $ 100,000 to $ 135,558 year)
The average salary range is between $ 91,891 and $ 135,005 year , with the average salary hovering around $ 107,281 year .
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Remote Senior SQL Engineer - AI Trainer
SuperAnnotateChesapeake, Virginia, US- Full-time
- Remote
As a Senior SQL Engineer, you will work remotely on an hourly paid basis to review AI-generated SQL queries, database designs, and data-processing logic, as well as generate high-quality reference solutions and explanations for complex data problems. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify errors in methodology, query structure, indexing strategy, or conceptual understanding; fact-check data-related claims; write clear, step-by-step explanations and model solutions that demonstrate correct methods; and rate and compare multiple AI responses based on correctness, performance, and reasoning quality.
This is a fully remote, hourly paid contractor role 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. Your SQL and database engineering expertise will directly contribute to improving the world’s premier AI models used across industries.
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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