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Ruby developer Jobs in Ann Arbor, MI
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Ruby developer • ann arbor mi
Remote Ruby Engineer - AI Trainer
SuperAnnotateAnn Arbor, Michigan, USSoftware Engineer Developer Productivity
Applied IntuitionAnn Arbor, Michigan, USAUnifier Developer Consultant
PyrovioAnn Arbor, Michigan, United StatesReact Developer
WebFXAnn Arbor, MI, United States.Net Developer III
Domino's CorporateAnn Arbor, MI, USDeveloper
SSGAnn Arbor, Michigan, USAReact Developer
webfx.comAnn Arbor, MI, USJava Developer
US Tech SolutionsAnn Arbor, MI, United StatesFull Stack Developer
NIRA DYNAMICS INCAnn Arbor, MI, USSalesforce Developer
The Judge GroupAnn Arbor, MIReact Developer
Webfx.comAnn Arbor, Michigan, United States- Promoted
Software Developer
Skill CorpAnn Arbor, MI, United StatesAzure Developer
MindSourceAnn Arbor, MI- Promoted
Software Developer
AquentAnn Arbor, MI, United StatesIntermediate-Senior Developer
Menlo InnovationsAnn Arbor, MI, United States- Promoted
Software Developer
SsgAnn Arbor, Michigan, United States- Promoted
- New!
Senior.NET Developer
Syms Strategic Group, LLC (SSG)Ann Arbor, MI, United States- Promoted
Remote Side Hustle Developer
Finance BuzzYpsilanti, Michigan, USSoftware Developer Senior
University of MichiganAnn Arbor, Michigan, USThe average salary range is between $ 100,000 and $ 160,000 year , with the average salary hovering around $ 160,000 year .
- associate dentist (from $ 50,000 to $ 273,750 year)
- software product manager (from $ 179,300 to $ 250,000 year)
- software engineering manager (from $ 179,300 to $ 215,750 year)
- platform engineer (from $ 109,750 to $ 207,405 year)
- product management (from $ 121,138 to $ 205,000 year)
- mental health associate (from $ 42,793 to $ 199,455 year)
- automotive engineer (from $ 110,000 to $ 196,000 year)
- attorney (from $ 67,500 to $ 192,500 year)
- infrastructure engineer (from $ 70,000 to $ 191,800 year)
- computer scientist (from $ 110,899 to $ 191,638 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
SuperAnnotateAnn Arbor, Michigan, 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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