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Ruby developer Jobs in Virginia Beach, VA
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Ruby developer • virginia beach va
Remote Ruby Engineer - AI Trainer
SuperAnnotateVirginia Beach, Virginia, USApplications Developer
QVineNorther Virginia VAApplication Developer
Apex SystemsVirginia Beach, VA.Net Developer
GDIT(VAHOME), Office, Home, VA, USAShift Leader-Virginia Beach-2849
ruby-tuesdayVirginia Beach, VA- Promoted
Training Curriculum Developer
Clearance JobsVirginia Beach, VA, USServiceNow Admin / Developer
APN ConsultingVirginia Beach, VA, United States.NET Developer
TechnoveraVirginia Beach, VASenior Ruby on Rails Developer
JobotVirginia Beach, VA, US- Promoted
Software Developer
SsgVirginia Beach, Virginia, United States- New!
Senior.NET Developer
Syms Strategic Group, LLC (SSG)Virginia Beach, VA, USM365 Developer
CACI InternationalVirginia Beach, VA, United StatesFrontend Developer (AngularJS)
SynergisticITVirginia Beach, VA, United StatesSr..Net Developer
SSGVirginia Beach, Virginia, USA- Promoted
Web Developer
VirtualVocationsVirginia Beach, Virginia, United States- Promoted
Snowflake Developer Lead / Architect
Veterans Sourcing Group LLCVirginia Beach, VA, United StatesApplication Developer
AbacusVirginia Beach, VA, United States- Promoted
Remote Side Hustle Developer
Finance BuzzVirginia Beach, Virginia, USJr..NET Developer
Staffing the UniverseVirginia Beach, VA, United StatesThe average salary range is between $ 109,625 and $ 168,188 year , with the average salary hovering around $ 135,000 year .
- pediatric dentist (from $ 49,688 to $ 325,000 year)
- quantitative developer (from $ 174,313 to $ 245,000 year)
- vp engineering (from $ 165,000 to $ 244,850 year)
- environmental economist (from $ 164,320 to $ 242,800 year)
- vp of engineering (from $ 150,000 to $ 241,500 year)
- psychiatrist (from $ 130,000 to $ 239,729 year)
- associate dentist (from $ 156,000 to $ 230,000 year)
- engineering director (from $ 125,000 to $ 229,696 year)
- design director (from $ 90,750 to $ 225,200 year)
- technical program manager (from $ 136,992 to $ 221,400 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
SuperAnnotateVirginia Beach, Virginia, 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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