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Freelance Machine Learning Data Annotation Jobs (NOW HIRING)

Abaka AI

Machine Learning Engineer

Mountain View, CA · On-site

... data workflows, including collection, preprocessing, annotation, versioning, and model integration. • Implement and refine training strategies for large-scale AI systems, including vision, video ...

Coalition, Inc.

WV · On-site

$200K/yr

About the role Coalition's machine learning models are only as good as the data they're trained on ... Define annotation guidelines, taxonomies, and edge-case protocols for each labeling program.

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Coordinate data collection and annotation efforts. * Work with real-time data and content coming from various data sources. * Manage machine learning data pipelines. * Design tests for machine ...

NTENT

Machine Learning Engineer

Carlsbad, CA

Coordinate data collection and annotation efforts. * Work with real-time data and content coming from various data sources. * Manage machine learning data pipelines. * Design tests for machine ...

Outpost

Machine Learning Data Engineer

Seattle, WA · On-site

$125 - $150/hr

Experience with dataset annotation/labeling tools and workflows (Roboflow, Labelbox, CVAT, or ... Experience with continuous learning or active learning pipelines for production ML systems.

Outpost

Machine Learning Data Engineer

Seattle, WA · Remote

$130K - $160K/yr

Experience with dataset annotation/labeling tools and workflows (Roboflow, Labelbox, CVAT, or ... Experience with continuous learning or active learning pipelines for production ML systems.

PROPRIUS

Machine Learning / Data Scientist

Bodega Bay, CA · On-site

$110K - $140K/yr

Job Summary Our client is looking for a machine learning engineer to join our existing ML team in developing and refining a predictive application. The ideal candidate is adept at using large data ...

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Freelance Machine Learning Data Annotation information

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How much do freelance machine learning data annotation jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for freelance machine learning data annotation in the United States is $21.87, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $25.00 per hour, depending on experience, location, and employer.

What is freelance machine learning data annotation?

Freelance machine learning data annotation involves labeling or tagging data—such as images, text, audio, or video—to help train machine learning models. As a freelancer, you work independently or through platforms, completing specific annotation tasks assigned by companies or researchers. This work is essential because high-quality labeled data is required for AI systems to learn and make accurate predictions. Annotators may categorize images, transcribe speech, or highlight relevant information in documents. The flexibility of freelancing allows you to choose projects and work remotely.

What are the key skills and qualifications needed to thrive as a freelance machine learning data annotation specialist?

To thrive as a Freelance Machine Learning Data Annotation specialist, you need attention to detail, basic knowledge of data labeling concepts, and familiarity with machine learning data types. Experience with annotation tools (such as Labelbox, RectLabel, or CVAT) and understanding of data privacy protocols are commonly required. Strong communication, time management, and the ability to follow complex guidelines are essential soft skills for delivering accurate results. These skills ensure high-quality, consistent data annotation, which is critical for effective machine learning model training and performance.

What are some common challenges faced by freelance machine learning data annotators, and how can they be managed?

Freelance machine learning data annotators often encounter challenges such as maintaining data accuracy, handling repetitive tasks, and understanding complex annotation guidelines. Staying organized and regularly reviewing project instructions can help ensure consistency and quality in annotations. Additionally, communicating proactively with project managers and utilizing annotation tools efficiently can help manage workload and clarify uncertainties. Building expertise in different data types (text, image, audio) also allows annotators to diversify their projects and reduce monotony.

What is the difference between Freelance Machine Learning Data Annotation vs Data Labeler?

AspectFreelance Machine Learning Data AnnotationData Labeler
CredentialsBasic understanding of annotation tools, sometimes with specialized domain knowledgeTypically no formal credentials required
Work EnvironmentRemote, flexible, project-basedOften remote or in-house, depending on employer
Industry UsageUsed in AI/ML development for training datasetsUsed in data preparation for various industries, including AI
Search/Comparison IntentFocuses on freelance opportunities, project scope, and toolsMore general, often employed by companies for data labeling tasks

Freelance Machine Learning Data Annotation involves independently completing annotation tasks for AI models, often with specialized tools and domain knowledge. Data Labelers typically perform similar tasks but may work as employees or contractors within a company. The main difference lies in the freelance nature and project-based work of data annotation roles.

Can I work for freelance machine learning data annotation with no experience?

Freelance machine learning data annotation jobs often do not require prior experience, as many tasks involve simple labeling or categorization that can be learned quickly. Basic computer skills, attention to detail, and familiarity with annotation tools are helpful, and training is usually provided. However, building a portfolio or gaining some familiarity with data annotation platforms can improve job prospects.
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Freelance Machine Learning Data Annotation jobs near you
Infographic showing various Freelance Machine Learning Data Annotation 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 $45,483 per year, or $21.9 per hour.

Data Annotation Specialist - South Bay, CA (On Site)

Welocalize

Menlo Park, CA • On-site

Full-time

Re-posted 6 days ago

Welocalize rating

6.5

Company rating: 6.5 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

340th of 500 rated business services

Job description

Job Summary:
Welo Data is looking for a skilled Data Analyst to join their team and contribute to advancing AI technologies. This role offers a unique opportunity to engage directly with cutting-edge AI products, supporting the refinement and performance of machine learning models through precise data analysis and quality assurance.
Responsibilities:
• Test new AI products and provide actionable feedback to improve functionality and user experience.
• Conduct detailed data annotation and quality assurance of natural language datasets following established guidelines.
• Collaborate in updating and refining machine learning models to boost accuracy and effectiveness.
• Analyze data for consistency, relevancy, and alignment with project goals.
• Perform quality control to identify and report anomalies, error patterns, and discrepancies.
• Use basic data analysis methods to extract insights and support continuous improvement.
• Prepare clear and concise reports on findings, including observations on data quality, AI model performance, and user feedback.
Qualifications:
Required:
• Must have valid work authorization in the US (Welocalize does not sponsor VISAs at this time).
• Test new AI products and provide actionable feedback to improve functionality and user experience.
• Conduct detailed data annotation and quality assurance of natural language datasets following established guidelines.
• Collaborate in updating and refining machine learning models to boost accuracy and effectiveness.
• Analyze data for consistency, relevancy, and alignment with project goals.
• Perform quality control to identify and report anomalies, error patterns, and discrepancies.
• Use basic data analysis methods to extract insights and support continuous improvement.
• Prepare clear and concise reports on findings, including observations on data quality, AI model performance, and user feedback.
Preferred:
• University degree in linguistics, translation, or a related field.
• 3-5 years of professional linguistics experience.
• Strong analytical skills with the ability to detect patterns and anomalies.
• Excellent communication skills and the ability to work collaboratively in a fast-paced environment.
• Adaptability to evolving priorities and project requirements.
Company:
Welocalize provides translation supply chain management solutions that deliver market-ready, translated content. Founded in 1997, the company is headquartered in Frederick, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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