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Korean Advanced Ai Data Trainer Jobs (NOW HIRING)

Advanced Data Analytics * Apply statistical modeling, signal processing, denoising, and feature ... Improve model accuracy through iterative training, active learning, and few-shot learning ...

$70 - $206/hr

You Are As a Snowflake Advanced AI Engineer, you will design, build, and operationalize artificial ... data and MLOps/LLMOps pipelines for training and production, and ensuring quality, value, and ...

You Are As a Snowflake Advanced AI Engineer, you will design, build, and operationalize artificial ... data and MLOps/LLMOps pipelines for training and production, and ensuring quality, value, and ...

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Korean Advanced Ai Data Trainer information

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How much do korean advanced ai data trainer jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for korean advanced ai data trainer in the United States is $31.24, according to ZipRecruiter salary data. Most workers in this role earn between $19.95 and $35.58 per hour, depending on experience, location, and employer.

What is a Korean Advanced AI Data Trainer?

A Korean Advanced AI Data Trainer is a professional who helps train artificial intelligence systems by providing, labeling, and reviewing data in the Korean language. They ensure that AI models understand and process Korean accurately by curating high-quality datasets, correcting outputs, and giving detailed feedback. This role often involves tasks such as annotating text, evaluating AI responses, and improving language models for applications like chatbots, translation, or voice assistants. Advanced trainers typically possess strong linguistic skills and a deep understanding of both AI technology and the nuances of the Korean language.

What does a Korean Advanced AI Data Trainer do?

As a Korean Advanced AI Data Trainer, your daily responsibilities often involve annotating and curating data in Korean, reviewing machine-generated outputs for linguistic accuracy, and providing feedback to improve AI language models. You'll regularly collaborate with data scientists, engineers, and other language experts to discuss project requirements, resolve ambiguities, and ensure data quality standards are met. The role requires attention to detail, a strong understanding of Korean language nuances, and effective communication with both technical and non-technical team members.

What skills and qualifications are needed to be a Korean Advanced AI Data Trainer?

To excel as a Korean Advanced AI Data Trainer, you need advanced Korean language proficiency, strong analytical abilities, and a background in linguistics or data science. Familiarity with annotation platforms, data labeling tools, and machine learning systems is often required, along with relevant certifications or experience. Attention to detail, critical thinking, and effective communication are vital soft skills for ensuring data quality and collaborating with technical teams. These competencies are crucial for producing high-quality datasets that enable accurate AI model training and performance.

What is the difference between Korean Advanced Ai Data Trainer vs Korean Ai Data Annotator?

AspectKorean Advanced Ai Data TrainerKorean Ai Data Annotator
CredentialsTypically requires specialized training in AI, data science, or related fieldsUsually requires basic data annotation skills, often on-the-job training
Work EnvironmentCollaborates with AI development teams, often in tech companies or research labsWorks primarily on labeling and annotating data, often in a more isolated setting
Industry UsageUsed in AI model training, especially for language and speech processing in KoreanUsed for preparing datasets for AI models, including image, text, and speech annotation

The Korean Advanced Ai Data Trainer typically has more specialized skills and works closely with AI development teams to improve model performance. In contrast, the Korean Ai Data Annotator focuses on labeling data to create training datasets. Both roles are essential in AI development, but the trainer usually requires more advanced knowledge and responsibilities.

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Infographic showing various Korean Advanced Ai Data Trainer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $64,984 per year, or $31.2 per hour.

AI Data Scientist

Prosum Inc.

Phoenix, AZ โ€ข On-site

Other

Re-posted 21 hours ago


Job description

Job Description
Our client is seeking an AI Data Scientist for a direct hire opportunity in North Phoenix, AZ or Hillsboro, OR. This role sites onsite 4 days a week and 1 day will be remote.
The AI Data Scientist will focus on developing state-of-the-art Automated Defect Classification (ADC) and Die-to-Database (DB) comparison algorithms, transforming advanced mathematical modeling into real-world industrial intelligence.
ESSENTIAL DUTIES AND RESPONSIBILITIES
Algorithm & Model Development
  • Design, train, and optimize deep learning and computer vision models for automated defect detection and classification.
  • Develop object detection and image classification algorithms to identify micro-scale defects such as particles, scratches, and pattern anomalies.
Die-to-Database (DB) Comparison
  • Develop high-precision image registration, geometric alignment, and image matching algorithms to compare captured optical images against CAD database layouts.
  • Improve alignment accuracy and robustness under varying imaging conditions.
Advanced Data Analytics
  • Apply statistical modeling, signal processing, denoising, and feature extraction techniques to improve image quality and inspection accuracy.
  • Analyze large, noisy datasets to optimize signal-to-noise ratio and model performance.
Model Development & Continuous Improvement
  • Evaluate model performance using real-world inspection data and analyze edge cases.
  • Improve model accuracy through iterative training, active learning, and few-shot learning techniques.
  • Collaborate with software engineers, field application teams, and domain experts to deploy and validate production-ready AI models.
Miscellaneous Responsibilities
  • Document algorithms, experiments, and model performance results.
  • Participate in code reviews, technical discussions, and knowledge sharing.
  • Assist with data preparation, annotation, validation, and quality assurance.
  • Stay current with advances in computer vision, machine learning, and AI technologies.
  • Collaborate with cross-functional teams to support product development and model deployment.
  • Perform other duties as assigned.

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