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Ai Labeler Jobs (NOW HIRING)

AST SpaceMobile

AI Lab Manager

Midland, TX

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Train labelers on AST's in-house image-labeling software, including labeling conventions, ontology updates, quality standards, escalation paths, and productivity expectations * Monitor labeling ...

Vadum Inc

Data Labeling Specialist

Raleigh, NC · On-site

$12 - $15/hr

We are seeking a detail-oriented Data Labeling Specialist temporarily (6 months) to support image ... Familiarity with AI, machine learning, or annotation tools is a plus, but not required. Physical ...

Vadum Inc

Data Labeling Specialist

Raleigh, NC

$12 - $15/hr

Description We are seeking a detail-oriented Data Labeling Specialist temporarily (6 months) to ... Familiarity with AI, machine learning, or annotation tools is a plus, but not required. Physical ...

AST SpaceMobile

AI Lab Manager

Midland, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Train labelers on AST's in-house image-labeling software, including labeling conventions, ontology updates, quality standards, escalation paths, and productivity expectations * Monitor labeling ...

Vadum, Inc.

Data Labeling Specialist

Raleigh, NC · On-site

$10/hr

We are seeking a detail-oriented Data Labeling Specialist temporarily (6 months) to support image ... Familiarity with AI, machine learning, or annotation tools is a plus, but not required. Physical ...

Skild AI

Computer Vision AI & ML Engineer

San Mateo, CA · On-site

$127K - $150K/yr

... labeling strategies and tooling for automated annotation, QA workflows, dataset management ... Skild AI develops artificial intelligence systems that enable robots to act in physical ...

Innodata Inc.

Generative AI Associate

$15/hr

We're on the lookout for smart, savvy, and curious Generative AI Specialist to join our global ... Labeling elements of a piece of content rather than the content as a whole. * Assigning predefined ...

Weekday AI

Project Coordinator - AI & Data Projects

$45 - $70/hr

Previous project or program coordination experience within AI, machine learning, data labeling, model evaluation, or research operations . * Experience supporting AI or data programs at large ...

New

Create Music Group

Staff AI Engineer

Los Angeles, CA · On-site

The company operates as a record label, distribution company, and entertainment network which ... Job Summary This Staff AI Engineer role sits at the intersection of AI systems architecture and ...

Innodata Inc.

Generative AI Associate

$15/hr

We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to ... Labeling elements of a piece of content rather than the content as a whole. * Assigning predefined ...

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Ai Labeler information

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How much do ai labeler jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for ai labeler in the United States is $13.97, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $15.38 per hour, depending on experience, location, and employer.

What is an AI labeler?

AI Labelers are professionals who annotate and categorize data, such as images, text, or audio, to help train artificial intelligence and machine learning models. Their work involves identifying objects, tagging features, or providing relevant context so that algorithms can learn to recognize patterns and make accurate predictions. This role is crucial for ensuring that AI systems are trained on high-quality, accurately labeled data, which directly impacts the performance and reliability of the resulting models.

What skills and qualifications are needed to thrive as an AI labeler?

To thrive as an AI Labeler, you need strong attention to detail, basic data entry skills, and familiarity with guidelines for annotating or categorizing data. Experience with labeling platforms, annotation tools, and sometimes basic knowledge of programming languages or image/audio editing software may be required. Reliability, consistency, and the ability to follow detailed instructions are important soft skills in this role. These skills ensure high-quality labeled datasets, which are essential for training accurate and effective AI models.

What are common challenges faced by AI labelers, and how can they be overcome?

AI Labelers often encounter challenges such as ambiguous data, balancing speed with accuracy, and maintaining consistency across large datasets. To overcome these, it's important to follow detailed guidelines provided by the company and ask for clarification when instructions are unclear. Regular feedback sessions with team leads or quality assurance specialists help labelers improve accuracy and stay aligned with project standards. Collaborating closely with other labelers and participating in training can also enhance consistency and reduce errors.
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Ai Labeler jobs near you
Infographic showing various Ai Labeler job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution, with an average salary of $29,053 per year, or $14 per hour.

AI Quality Infrastructure Engineer

Tror AI for everyone

Mountain View, CA • On-site

$126K - $166K/yr

Contractor

Re-posted 7 days ago

Job description

Job Role: AI Quality Infrastructure Engineer

Job Location: MTV, CA or San Diego, CA or NYC, NY or Remote

Job Duration: Long Term Contract

Overview:

As an AI Quality Infrastructure Engineer, you will build quality infrastructure and build quality pipelines with these to guarantee the reliability of our AI ecosystem. You won’t just monitor models; you will build the automated systems that make monitoring possible at scale. You will be responsible for engineering the "LLM-as-a-judge" services, custom observability frameworks, and the automated alerting logic that connects our AI agents to our production response teams. Your work will bridge the gap between AI research and production-grade reliability engineering.

What the Job Entails

  • Build Automated Quality Tooling for AI: Build and maintain internal tools and services that automate the measurement of quality for the AI and AI agent development lifecycle. This includes the development of quality coverage tools for prompt-based approaches, creating testing automation pipelines to support tool call validations, and the "LLM-as-a-judge" scoring engines.
  • Build Production Monitoring Tooling: Build and maintain internal tools the ensure continuous production monitoring with synthetic test for our AI capabilities.
  • Design Synthetic Data Generators: Build tools to programmatically generate high-fidelity synthetic datasets for continuous stress-testing and "golden set" benchmarking.
  • Labeling tools: Build and maintain rapid labeling pipelines for AI Agents.
  • Engineer Observability Pipelines: Develop the backend data pipelines that stream model logs, tool-calling traces, and metadata into Splunk and Amplitude for real-time visualization.
  • Automate Alerting & Incident Response: Write the logic and scripts to programmatically trigger PagerDuty incidents based on complex model performance thresholds and data quality anomalies.
  • Develop Data Quality Services: Create automated services to detect data drift and non-natural language patterns (e.g., input feature distributions or sentiment shifts) before they impact the user.
  • Scalable ML Tooling: Eventually design and build the infrastructure for end-to-end Machine Learning pipelines, focusing on automated training data validation and model-check gatekeeping.

Our Ideal Candidate:

  • Education: Bachelor’s or Master’s Degree in Computer Science, Software Engineering, or a related technical field.
  • Engineering Proficiency: Expert-level Python and SQL skills with a focus on building reusable libraries, APIs, and automation scripts.
  • Monitoring-as-Code: Experience in "Monitoring-as-Code," including programmatically configuring Splunk alerts, Amplitude, and PagerDuty services.
  • AI/ML Infrastructure: Strong understanding of LLM architectures and the engineering challenges of testing non-deterministic systems.
  • System Design Mindset: Ability to design scalable, fault-tolerant systems that can handle millions of AI conversation traces without latency.
  • Problem Solving: A "builder" mentality—you see a manual process and your first instinct is to write code to automate.
 
Thanks & Regards
Akhil
akhil@tror.ai