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Javascript developer Jobs in Los Angeles, CA
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Javascript developer • los angeles ca
Remote JavaScript Engineer - AI Trainer
SuperAnnotateMontebello, California, USBusiness Developer
COALITION FOR RESPONSIBLE COMMUNITY DEVLos Angeles, CA, US- Promoted
Angular Developer
Cynet SystemsLos Angeles, CA, USAndroid Developer
Black Rock Solutions CorporationLos Angeles, CA, USTableau Developer
Arena StaffingLos Angeles, California, USAJava Developer
InnoventricsLos Angeles, CA, USJavaScript Fullstack Engineer
VirtualVocationsDowney, California, United States- Promoted
Full Stack Engineer with JavaScript and Python
Stealth StartupWoodland Hills, California, United StatesServiceNow Developer
Contact Government Services, LLCLos Angeles, CA, USSenior Web / JavaScript Engineer (R50029978)
Fox CorporationLos Angeles, CaliforniaSenior Full Stack JavaScript Engineer / Hybrid in Santa Monica
Motion RecruitmentLos Angeles, California, United States- Promoted
Relationship Manager, Construction Lending
Ascent Developer SolutionsEncino, CA, US- Promoted
Salesforce Developer
TECHOHANALos Angeles, CA, USFrontend Developer -React / JavaScript
Sourcing ScreenLos Angeles, CA, USSFDC Developer
TekWissen LLCWoodland Hills, California, USAtutor - JavaScript programming
BUKILos Angeles, CA, USWeb Developer
Enthusiast Auto HoldingsLos Angeles, California, United States- Promoted
Web Developer
TradeJobsWorkForce90010 Los Angeles, CA, US- Promoted
Fullstack Developer
California StaffingLos Angeles, CA, USThe average salary range is between $ 105,000 and $ 160,000 year , with the average salary hovering around $ 120,600 year .
- team owner operator (from $ 154,700 to $ 430,600 year)
- anesthesiologist (from $ 52,833 to $ 420,000 year)
- trauma surgeon (from $ 63,220 to $ 396,075 year)
- orthopaedic surgeon (from $ 160,185 to $ 350,000 year)
- hospitalist (from $ 75,000 to $ 280,000 year)
- general surgeon (from $ 50,000 to $ 275,000 year)
- dermatologist (from $ 43,350 to $ 270,000 year)
- thoracic surgeon (from $ 237,979 to $ 265,679 year)
- chief sustainability officer (from $ 201,765 to $ 264,014 year)
- industrial production manager (from $ 59,456 to $ 250,000 year)
- New York, NY (from $ 100,000 to $ 164,890 year)
- Los Angeles, CA (from $ 105,000 to $ 160,000 year)
- Chicago, IL (from $ 110,000 to $ 157,200 year)
- Houston, TX (from $ 105,000 to $ 150,000 year)
- Philadelphia, PA (from $ 97,500 to $ 137,783 year)
- Phoenix, AZ (from $ 105,000 to $ 135,000 year)
- Birmingham, AL (from $ 42,500 to $ 131,282 year)
- Vancouver, WA (from $ 108,750 to $ 125,000 year)
The average salary range is between $ 96,922 and $ 150,205 year , with the average salary hovering around $ 117,000 year .
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Remote JavaScript Engineer - AI Trainer
SuperAnnotateMontebello, California, US- Full-time
- Remote
As an hourly paid, fully remote JavaScript Engineer for AI Data Training, you will review complex AI-generated code and explanations or generate new ones, 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 accuracy, clarity, and adherence to the prompt, identify errors in methodology or conceptual understanding, fact-check 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 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. 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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