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Ruby developer Jobs in Winston-Salem, NC
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Ruby developer • winston salem nc
Remote Ruby Engineer - AI Trainer
SuperAnnotateWinston, North Carolina, US.Net Developer
RIA Solutions GroupWinston-Salem, NC, United StatesSr. Enterprise Applications Developer
AmarrWinston-Salem, NCNC - UNC System - Senior Tableau Developer
MahantechNorth Carolina, USAAngularJS Developer - Work from home
TEKsystemsWinston Salem, NC, USAION Application Developer
Syntricate TechnologiesWinston-Salem, NC, United StatesPython Developer (Entry Level)
SynergisticITWinston-Salem, NC, United StatesSoftware Support Developer
Brock SolutionsWinston SalemSenior Back End Developer
CoLabWinston-Salem, NC, United States- Promoted
Senior Cognos Developer / BI Developer (Cognos)
Aroha TechnologiesWallburg, North Carolina, United StatesSr. Java Developer
Contact Government Services, LlcWinston-Salem, North Carolina, United StatesPython Developer-Remote
Staffing the UniverseWinston-Salem, NC, United StatesSoftware Developer
SsgWinston-Salem, North Carolina, United StatesFull Stack Developer
Cloud Security CorporationWinston-Salem, NC, United States- Promoted
Remote Side Hustle Developer
Finance BuzzClemmons, North Carolina, USSenior Full-stack Developer (Python + React)
IntellectsoftWinston-Salem, NC, United StatesSr. OneStream Developer (hybrid)
Herbalife-International-of-AmericaSalem, Winston, NC, USSenior SAP MII Developer
Symbiotic ServicesWinston-Salem, NC, USDeveloper (Sales Rep) - Winston-Salem, NC
Pratt Retail SpecialtiesWinston Salem, NCThe average salary range is between $ 115,000 and $ 127,500 year , with the average salary hovering around $ 121,250 year .
- general dentist (from $ 25,000 to $ 250,000 year)
- technical program manager (from $ 143,650 to $ 228,000 year)
- design director (from $ 154,525 to $ 226,375 year)
- machine learning engineer (from $ 117,160 to $ 221,526 year)
- vp engineering (from $ 200,000 to $ 220,250 year)
- engineering director (from $ 165,675 to $ 212,160 year)
- software development manager (from $ 88,008 to $ 211,494 year)
- engineering program manager (from $ 100,238 to $ 209,500 year)
- cyber security (from $ 99,723 to $ 208,000 year)
- Bend, OR (from $ 163,954 to $ 180,000 year)
- San Jose, CA (from $ 125,000 to $ 175,500 year)
- San Francisco, CA (from $ 125,000 to $ 175,500 year)
- San Mateo, CA (from $ 125,000 to $ 175,500 year)
- New Bedford, MA (from $ 117,000 to $ 175,000 year)
- New Orleans, LA (from $ 117,000 to $ 175,000 year)
- Santa Clara, CA (from $ 121,250 to $ 173,350 year)
- Oakland, CA (from $ 110,790 to $ 172,640 year)
- Chattanooga, TN (from $ 132,500 to $ 171,200 year)
- Fort Collins, CO (from $ 105,000 to $ 171,000 year)
The average salary range is between $ 107,285 and $ 164,719 year , with the average salary hovering around $ 130,000 year .
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Remote Ruby Engineer - AI Trainer
SuperAnnotateWinston, North Carolina, US- Full-time
- Remote
As an hourly paid, fully remote Ruby Engineer for AI Data Training, you will review AI-generated Ruby and Rails code or generate your own solutions, evaluate the reasoning quality and step-by-step problem-solving, and provide expert feedback that helps models produce answers that are accurate, logical, and clearly explained. You will assess solutions for readability, maintainability, and correctness; identify errors in MVC structure, domain modeling, or control flow; fact-check information; write high-quality explanations and model solutions that demonstrate idiomatic Ruby patterns; and rate and compare multiple AI responses based on correctness and reasoning quality.
This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate that provides AI training data for many of the world’s largest AI companies and foundation model labs, and your work will directly help improve the world’s premier AI models while giving you the flexibility of impactful, detail-oriented remote contract work.
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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