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Machine Learning Data Annotation Jobs (NOW HIRING)

$70 - $90/hr

Your mission & challenges As an AI Data Annotation Specialist, you will operate at the intersection of data ingestion, processing, and machine learning. Your primary responsibility is to design and ...

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 ...

Data Labeling Associate

$16.50 - $21.25/hr

Modify and refine machine learning data creation, annotation, and rating guidelines. Model Training and Evaluation: * Initiate model training processes using internal tools and command-line ...

Data Labeling Associate

New York, NY

$17.50 - $22.75/hr

Modify and refine machine learning data creation, annotation, and rating guidelines. Model Training and Evaluation: * Initiate model training processes using internal tools and command-line ...

Data Labeling Associate

San Diego, CA

$17 - $22/hr

Modify and refine machine learning data creation, annotation, and rating guidelines. Model Training and Evaluation: * Initiate model training processes using internal tools and command-line ...

Data Labeling Associate

New York, NY

$17.50 - $22.75/hr

Modify and refine machine learning data creation, annotation, and rating guidelines. Model Training and Evaluation: * Initiate model training processes using internal tools and command-line ...

Familiarity with AI and machine learning concepts. Additional language skills, which are beneficial for multilingual data annotation projects. Proven track record of handling confidential and ...

$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 ...

Manage and coach a team of Machine Learning Data Domain analysts to support data annotation and label data/content using annotation tools and analysis * Partner with leads in Data Science ...

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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.

More about Machine Learning Data Annotation jobs

What are the most commonly searched types of Machine Learning Data Annotation jobs?

The most popular types of Machine Learning Data Annotation jobs are:

Infographic showing various 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 85% Physical, 4% Hybrid, and 11% Remote job distribution.

AI Data Annotation Specialist (human)

On-site

$70 - $90/hr

Other

Posted 7 days ago


Job description

Your mission & challenges

As an AI Data Annotation Specialist, you will operate at the intersection of data ingestion, processing, and machine learning. Your primary responsibility is to design and maintain scalable workflows for automated data annotation, while ensuring that datasets are properly validated, standardized, and formatted for efficient model training.

You play a critical role in enabling high-quality AI systems by transforming raw data into structured, reliable training datasets.

  • Design, build, and maintain pipelines for automated and semi-automated data annotation
  • Ingest and integrate data from multimodal sources into structured data workflows
  • Apply pre-labeling techniques using existing models to accelerate annotation processes
  • Validate and ensure the quality, consistency, and completeness of annotated datasets
  • Identify and resolve data quality issues, inconsistencies, and biases
  • Transform and standardize datasets into model-ready formats
  • Collaborate closely with ML Engineers to optimize datasets for training and evaluation
What we can look forward to
  • Degree in Computer Science, Data Science, Engineering, or a related field
  • 3+ years of experience in machine learning operations, AI, or software engineering
  • Strong programming skills in Python and C++
  • Solid understanding of AI / machine learning fundamentals and data requirements
  • Experience with data annotation tools or labeling workflows
  • Familiarity with dataset structuring and formatting for ML frameworks (e.g., robotics datasets, multimodal data)
  • Strong attention to detail and a quality-driven mindset
  • Experience with cloud platforms (AWS, GCP, Azure) is a plus
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