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Ai Trainers Jobs (NOW HIRING)

Kake Group

Senior AI Talent Sourcer

Austin, TX · Remote

Identify, engage, and nurture specialized talent including AI trainers, evaluators, machine learning engineers, research engineers, AI researchers, domain experts, and other specialists contributing ...

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How much do ai trainers jobs pay per hour?

As of Jun 16, 2026, the average hourly pay for ai trainers in the United States is $29.33, according to ZipRecruiter salary data. Most workers in this role earn between $19.47 and $31.49 per hour, depending on experience, location, and employer.

What is the difference between Ai Trainers vs Data Annotators?

AspectAi TrainersData Annotators
Required CredentialsTypically a degree in computer science, AI, or related fields; familiarity with machine learning conceptsHigh school diploma or equivalent; training in annotation tools and guidelines
Work EnvironmentOffice or remote; collaborative with data scientists and engineersRemote or on-site; focused on labeling data according to instructions
Industry UsageAI development, machine learning projects, training AI modelsData preparation, dataset creation, improving model accuracy

Ai Trainers and Data Annotators both play vital roles in AI development. Ai Trainers focus on training models by providing labeled data and refining algorithms, often requiring technical knowledge. Data Annotators primarily label and categorize data to prepare datasets for AI systems. While their tasks overlap, Ai Trainers typically have more technical credentials and work closely with AI teams, whereas Data Annotators focus on data labeling tasks essential for model training.

What job makes $10,000 a month without a degree?

AI trainers can potentially earn $10,000 or more per month by training and fine-tuning artificial intelligence models, especially in freelance or high-demand environments. Success in this role depends on expertise in machine learning, data annotation, and familiarity with AI tools, often without requiring a formal degree but emphasizing skills and experience. Such roles may involve remote work and flexible schedules.

How can I get a job as an AI trainer?

To become an AI trainer, you typically need a background in computer science, data analysis, or related fields, along with skills in machine learning, natural language processing, and data annotation. Gaining experience with AI tools and platforms, such as TensorFlow or PyTorch, and understanding data labeling processes are also important. Certifications in AI or data science can enhance your prospects, and familiarity with programming languages like Python is often required.

What are AI trainers?

AI trainers are professionals who help develop and improve artificial intelligence systems by providing relevant data, feedback, and guidance. They label data, review AI outputs, and correct errors to ensure the technology learns accurately and performs as intended. AI trainers often work closely with data scientists and machine learning engineers to refine algorithms and enhance system performance. Their work is critical in making AI applications more reliable and effective in real-world scenarios.

What are some common challenges AI Trainers face when annotating and curating data, and how can they be addressed?

AI Trainers often encounter challenges such as ambiguous data, inconsistent labeling guidelines, and balancing quality with efficiency. These can be addressed by participating in regular calibration sessions with the team, maintaining clear and updated annotation guidelines, and leveraging quality assurance tools. Open communication with data scientists and engineers also helps clarify uncertainties and ensures high-quality, consistent datasets—critical to the success of AI models.

How much money do AI trainers make?

AI trainers typically earn between $50,000 and $120,000 annually, depending on experience, location, and the complexity of the projects. Entry-level positions may start lower, while experienced trainers with specialized skills in machine learning and data annotation can earn higher salaries. Many roles also offer benefits and opportunities for remote work.

What are the key skills and qualifications needed to thrive as an AI Trainer, and why are they important?

To thrive as an AI Trainer, you need a solid understanding of machine learning concepts, data annotation processes, and attention to detail, usually supported by a background in computer science or a related field. Familiarity with annotation tools, data labeling platforms, and sometimes basic programming or scripting languages is often required. Strong communication skills, critical thinking, and the ability to follow complex guidelines help AI Trainers excel in delivering high-quality data. These skills and qualities are crucial for ensuring accurate model training, which directly impacts the performance and reliability of AI systems.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles such as AI research directors, chief AI officers, or senior machine learning executives, often in large tech companies or startups. These positions usually require extensive experience, advanced skills in AI and data science, and may include stock options or bonuses that contribute to the total compensation. Such roles are rare and highly competitive, reflecting leadership in AI development and strategy.
Infographic showing various Ai Trainers job openings in the United States as of June 2026, with employment types broken down into 14% Full Time, 14% Part Time, and 72% Contract. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $61,014 per year, or $29.3 per hour.

Call Center Lead with AI-Tech support (AI implementation)

Imperial Management Administrators Services Inc

Pasadena, CA • Remote

Full-time

Posted 3 days ago

Job description

Job Summary:

We are seeking a highly organized and tech-savvy Call Center Supervisor to oversee the daily operations of AI-driven customer service agents. In this role, you will manage and optimize a hybrid contact center environment where AI agents handle first-tier customer interactions, escalating to human agents when necessary. You will play a critical role in monitoring AI performance, maintaining service quality, and ensuring a seamless customer experience across all support channels.

Key Responsibilities:

  • Supervise and Monitor AI Agents:
    Oversee the performance and accuracy of AI-powered customer service agents across voice, chat, and email channels.
  • Quality Assurance:
    Audit AI conversations to ensure compliance with company policies, brand voice, and regulatory requirements. Collaborate with AI trainers and data teams to fine-tune responses.
  • Issue Escalation & Resolution:
    Monitor AI escalations to human agents and ensure proper handoff and resolution. Identify and address patterns in escalations to improve AI handling capabilities.
  • Team Collaboration:
    Work closely with human support staff, AI trainers, developers, and data analysts to improve the overall efficiency and accuracy of AI agents.
  • Performance Analytics:
    Use dashboards and analytics tools to track AI KPIs such as first-contact resolution, containment rate, CSAT, and escalation rate. Provide regular reports to leadership.
  • Process Improvement:
    Identify operational bottlenecks and propose workflow or training enhancements for both AI and human agents.
  • Training & Feedback:
    Provide regular feedback to AI development teams based on customer interactions. Ensure updates to AI models are tested and implemented effectively.

Qualifications:

  • Experience:
    • 3+ years in a call center supervisory or operations role.
    • Experience working with or managing AI-powered support tools is highly preferred.
  • Skills:
    • Strong understanding of customer service metrics and tools (e.g., Zendesk, Salesforce, LivePerson, Intercom).
    • Familiarity with conversational AI platforms (e.g., GPT, Dialogflow, IBM Watson) is a plus.
    • Excellent problem-solving and decision-making skills.
    • Ability to interpret and communicate data insights clearly.
  • Technical Acumen:
    • Comfort with emerging technologies and AI tools.
    • Basic understanding of machine learning concepts and how AI models are trained/improved is a plus.
  • Education:
    • Bachelor’s degree in Business, Communications, Information Technology, or related field. Equivalent experience may be considered.