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Machine Learning Data Annotation Jobs (NOW HIRING)

Innodata Inc.

$55 - $60/hr

Bachelor's degree in Computer Science, Machine Learning, Data Science, or related field required ... CVAT annotation platform - AI feature configuration and operation * DoD or IC data program ...

Q Analysts

Data Annotation Technician

Kirkland, WA · On-site

Data Annotation Technician Join Q Analysts and become part of a world-class organization. Q ... AI) and machine learning (ML). Q Analysts is headquartered in San Jose, CA with a presence ...

YO AI Labs

Video Annotation Expert - Remote

Houston, TX · Remote

$50 - $90/hr

The role involves accurate video labeling and structured data annotation to support AI and machine-learning projects. Key Responsibilities * Review videos and identify key actions, events, and ...

New

YO AI Labs

Video Annotation Expert - Remote

Seattle, WA · Remote

$50 - $90/hr

The role involves accurate video labeling and structured data annotation to support AI and machine-learning projects. Key Responsibilities * Review videos and identify key actions, events, and ...

New

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Machine Learning Data Annotation information

What is machine learning data annotation?

Machine learning data annotation is the process of labeling or tagging data—such as images, text, audio, or video—so that it can be used to train machine learning models. Annotators add relevant information to raw data, helping algorithms learn to recognize patterns and make predictions. This process is essential for supervised learning, as models require accurately labeled datasets to achieve high performance. Data annotation can be done manually or with the help of specialized tools, and is a critical step in developing reliable AI systems.

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

To thrive as a Machine Learning Data Annotation Specialist, you need strong attention to detail, familiarity with data labeling processes, and a basic understanding of machine learning concepts, often supported by a relevant degree or specialized training. Experience with annotation platforms such as Labelbox, Supervisely, or CVAT, and knowledge of data management systems are commonly required. Diligence, consistency, and effective communication are essential soft skills for ensuring high-quality annotated datasets and collaborating with machine learning teams. These skills are crucial for producing accurate training data, which directly impacts the performance and reliability of AI models.

What are some common challenges faced in a machine learning data annotation role, and how can they be addressed?

One common challenge in a Machine Learning Data Annotation role is maintaining high consistency and accuracy, especially when dealing with large volumes of complex data. Ambiguities in labeling guidelines or unclear data points can also make the work more difficult. To address these issues, annotators often participate in regular training sessions, utilize detailed instruction manuals, and collaborate closely with quality assurance teams. Open communication with project managers and peers is also essential to clarify uncertainties and ensure alignment with project standards.

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

AspectMachine Learning Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech companies, AI projectsRemote or on-site, data processing centers, AI companies
Industry UsageAI, machine learning, data scienceData management, AI, machine learning
Job FocusCreating labeled datasets for training AI modelsLabeling data to assist AI training

Machine Learning Data Annotation involves creating detailed labels and annotations for datasets used to train AI models, often requiring understanding of specific data types. Data Labelers focus on applying labels to data, typically with less emphasis on complex annotations. Both roles are essential in AI development, but data annotation often involves more specialized tasks and tools.

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Machine Learning Data Annotation jobs near you
Infographic showing various Machine Learning Data Annotation job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 12% Part Time, and 2% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution.

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

Sunnyvale, CA • On-site

Welocalize
Translation Services • 1 - 5K employees
Learn more about Welocalizeexternal

Full-time

Re-posted 12 days ago

Welocalize rating

6.5

Company rating: 6.5 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

Job description

Job Summary:
Welo Data is a company focused on advancing AI technologies, and they are seeking a skilled Data Annotation Specialist to join their team. The role involves testing AI products, conducting data annotation, and ensuring high-quality data for machine learning models.
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).
• 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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Hours and flexibility

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