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Machine Learning Data Annotation Jobs (NOW HIRING)

Sunday Inc

Data Annotation Lead

Redwood City, CA · On-site

You'll work in coordination with Machine Learning, Software engineering, and Data to define the framework and tools on which to build a data annotation team around. Your role is vital to ensuring our ...

Innodata Inc.

Data & Annotation Engineer

Washington, DC · On-site

$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 ...

Welocalize, Inc.

Data Quality Analyst

New York, NY · On-site

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 ...

Welocalize, Inc.

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 ...

Welocalize, Inc.

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 ...

Welocalize, Inc.

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 ...

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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.

Can I do data annotation with no experience?

Machine Learning Data Annotation jobs often do not require prior experience, as training is typically provided. Basic skills such as attention to detail and familiarity with computers are sufficient to start, and some roles may require knowledge of annotation tools or platforms. Entry-level positions are common and suitable for beginners seeking to develop relevant skills.

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 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.

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.
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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 July 2026, with employment types broken down into 3% Locum Tenens, 23% Full Time, 28% Part Time, 1% Contract, 44% Nights, and 1% Summer. Highlights an 46% Physical, 1% Hybrid, and 53% Remote job distribution.

Atlas Data Operations Annotation Manager

Boston Dynamics

Waltham, MA • On-site

Full-time

Re-posted 5 days ago

Job description

Job Summary:
Boston Dynamics is a world leader in mobile robots, tackling some of the toughest robotics challenges. They are seeking a highly organized and technically-minded Annotation Manager to lead a team of Annotation Leads and QA Leads, manage relationships with third-party vendors, and ensure the quality and consistency of data annotations for Atlas's machine learning systems.
Responsibilities:
• Directly manage a team of Annotation Leads and Annotation QA Leads, providing day-to-day direction, prioritization, coaching, and performance feedback.
• Serve as the Atlas working team lead for third-party annotation vendors, managing task allocation, performance accountability, and dual-source relationships to optimize cost and quality.
• Own the end-to-end quality of annotation output by partnering with ML Leads to establish and enforce quality benchmarks, monitor throughput and error rate metrics, and serve as the primary escalation point for labeling guideline ambiguities.
• Write SOP’s and technical/process/policy documents for the annotation team to follow
• Forecast forward-looking annotation needs across all Atlas engineering stakeholders and drive continuous improvement initiatives including tooling feedback, workflow redesign, and SOP maintenance.
Qualifications:
Required:
• Proven experience managing teams in a data annotation or machine learning data pipeline environment required
• Strong familiarity with annotation concepts and tooling platforms
• Strong computer proficiency with familiarity in ML data pipelines or computer vision
• Exceptional organizational and communication skills required
Preferred:
• Bachelor's degree in a technical field, data science, or cognitive science preferred
• Prior experience managing third-party annotation vendors strongly preferred
Company:
Boston Dynamics is an engineering company that specializes in building dynamic robots and software for human simulation. It is a sub-organization of Hyundai Motor Company. Founded in 1992, the company is headquartered in Waltham, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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