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Ai Labeler Jobs (NOW HIRING)

Pareto AI

Applied AI Engineer

$225K - $275K/yr

Experience building human data labeling interfaces, annotation workflows, or data collection pipelines * Familiarity with preference data and reward models used in AI model training (RLHF, RLVR, or ...

Aerotek

Data Labeling Specialist

San Jose, CA · On-site

$30/hr

🚀 Data Labeling Specialist - AI & Robotics 💡 No prior experience required -- All training will be provided Join our mission to build the world's first general-purpose humanoid robot. As a Data ...

AST SpaceMobile

AI Lab Manager

Midland, TX · On-site

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

AST SpaceMobile

AI Lab Manager

Midland, TX

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

AST SpaceMobile

AI Lab Manager

Midland, TX · On-site

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

Skild AI

Computer Vision AI & ML Engineer

San Mateo, CA · On-site

$127K - $150K/yr

Skild AI is building the world's first general purpose robotic intelligence that adapts to unseen ... labeling strategies and tooling for automated annotation, QA workflows, dataset management ...

General Motors

Senior AI/ML Engineer

Bismarck, ND · On-site +1

$102K - $140K/yr

The Data Labeling Engineering team designs, builds, and operates hybrid human/machine data labeling ... We partner closely across AI/ML engineers , Product Operations , Product Management , Data Science ...

General Motors

Senior AI/ML Engineer

Jackson, MS · On-site +1

$91K - $125K/yr

The Data Labeling Engineering team designs, builds, and operates hybrid human/machine data labeling ... We partner closely across AI/ML engineers , Product Operations , Product Management , Data Science ...

General Motors

Senior AI/ML Engineer

Providence, RI · On-site +1

$105K - $145K/yr

The Data Labeling Engineering team designs, builds, and operates hybrid human/machine data labeling ... We partner closely across AI/ML engineers , Product Operations , Product Management , Data Science ...

General Motors

Senior AI/ML Engineer

Nashville, TN · On-site +1

$100K - $138K/yr

The Data Labeling Engineering team designs, builds, and operates hybrid human/machine data labeling ... We partner closely across AI/ML engineers , Product Operations , Product Management , Data Science ...

General Motors

Senior AI/ML Engineer

Richmond, VA · On-site +1

$103K - $142K/yr

The Data Labeling Engineering team designs, builds, and operates hybrid human/machine data labeling ... We partner closely across AI/ML engineers , Product Operations , Product Management , Data Science ...

General Motors

Senior AI/ML Engineer

Sunnyvale, CA · On-site

$122K - $168K/yr

The Data Labeling Engineering team designs, builds, and operates hybrid human/machine data labeling ... We partner closely across AI/ML engineers, Product Operations, Product Management, Data Science ...

General Motors

Senior AI/ML Engineer

Sacramento, CA · On-site +1

$113K - $156K/yr

The Data Labeling Engineering team designs, builds, and operates hybrid human/machine data labeling ... We partner closely across AI/ML engineers , Product Operations , Product Management , Data Science ...

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How much do ai labeler jobs pay per hour?

As of Jun 9, 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 are AI Labelers?

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

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 some 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 June 2026, with employment types broken down into 89% Part Time, and 11% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $29,053 per year, or $14 per hour.
Technical Lead Manager, Physical AI

Technical Lead Manager, Physical AI

Scale AI

San Francisco, CA • On-site

Full-time

Posted yesterday

Job description

Job Summary:
Scale AI is the data engine for the entire AI industry, focused on building general AI that can reason and act in the physical world. The Technical Lead Manager will lead a team of Research Engineers to develop and evaluate Large-Scale Foundation Models for Physical AI, bridging the gap between machine learning research and physical robot deployment.
Responsibilities:
• Direct research into scaling laws for Physical AI, determining how to best utilize massive datasets for pre-training and fine-tuning generalist policies.
• Develop novel methods for developing and evaluating models, including new Physical AI industry benchmarks
• Actively write code to implement, train and test SOTA architectures. Conduct research on Physical AI data collection, cross-embodiment training, and policy fine-tuning.
• Collaborate with internal labeling teams to design "robotic-native" data pipelines, including the use of VLMs for automated trajectory annotation and data synthesis.
• Collaborate closely with customers to drive the industry forward in using Scale data
• Lead and grow a team of 4-6 elite Physical AI researchers, fostering a culture of high-velocity experimentation and rigorous evaluation.
• Translate the latest research from NeurIPS, ICRA, and CVPR into production-ready features for Scale’s Physical AI partners.
• Work with cross-functional teams (e.g Product and Operations) to bring our research breakthroughs into production.
Qualifications:
Required:
• Expert-level proficiency in PyTorch, with deep knowledge of Transformer architectures, Attention mechanisms, and Self-Supervised Learning.
• Proven track record of working with Vision-Language Models (e.g., CLIP, PaLM-E) and adapting them for spatial reasoning or embodied tasks.
• Experience with Diffusion Models for sequence generation or Generative World Models for predictive modeling.
• Strong understanding of Physical AI stack, including imitation learning, reinforcement learning (RL), and multi-modal sensor fusion.
• Experience with large-scale distributed training across GPU clusters and high-performance data loading.
• 1+ years of experience leading technical teams or projects in a research-intensive environment.
Preferred:
• First-author publications at top-tier AI/ML conferences (NeurIPS, CVPR, ICRA, CoRL).
• Experience building models that work across different robot types (arms, mobile bases, humanoids).
• Experience with high-fidelity simulators (e.g., Isaac Gym, MuJoCo) and the nuances of physical domain adaptation.
Company:
Scale’s mission is to develop reliable AI systems for the world’s most important decisions. Founded in 2016, the company is headquartered in San Francisco, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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