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Contract Data Annotation Jobs in California (NOW HIRING)

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Contract Data Annotation information

What is the difference between Contract Data Annotation vs Data Labeler?

AspectContract Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, project-basedRemote or on-site, task-based
Industry UsageAI/ML training, tech companiesAI/ML training, tech companies
Job FocusAnnotating data for machine learning modelsLabeling data to improve AI algorithms

Contract Data Annotation involves completing specific annotation projects for AI training, often on a contractual basis. Data Labelers focus on labeling data to enhance machine learning models, typically performing similar tasks. Both roles require attention to detail and are used in AI/ML industries, but Contract Data Annotation emphasizes project-based work with defined deliverables.

What is a contract data annotation job?

A contract data annotation job involves labeling or tagging data—such as images, text, audio, or video—according to specific guidelines, usually on a temporary or project-based contract. These annotations help train machine learning models by providing accurate, human-labeled examples for algorithms to learn from. Contract workers are typically hired for a set period or project and may work remotely or on-site, depending on the employer. The work requires attention to detail, adherence to quality standards, and sometimes familiarity with specialized annotation tools.

What are the key skills and qualifications needed to thrive as a Contract Data Annotation Specialist, and why are they important?

To thrive as a Contract Data Annotation Specialist, you need a keen eye for detail, strong analytical skills, and familiarity with data labeling standards, often supported by experience in data management or related fields. Proficiency with annotation platforms (such as Labelbox, Prodigy, or CVAT) and basic knowledge of data formats like JSON or XML are commonly required. Excellent communication, time management, and the ability to work independently help individuals excel in this often remote and deadline-driven role. These skills ensure high-quality, accurate data annotations that are vital for training reliable machine learning models.

What are some common challenges faced by contract data annotation professionals, and how can they be effectively managed?

Contract data annotation professionals often encounter challenges such as maintaining consistency in labeling, managing tight project deadlines, and ensuring data privacy. These challenges can be effectively managed by following detailed annotation guidelines, utilizing collaborative tools for team communication, and participating in regular quality assurance checks. Staying organized and proactive about seeking clarification from project leads also helps ensure high-quality, accurate results and a smooth workflow.
What are the most commonly searched types of Data Annotation jobs in California? The most popular types of Data Annotation jobs in California are:
What job categories do people searching Contract Data Annotation jobs in California look for? The top searched job categories for Contract Data Annotation jobs in California are:
What cities in California are hiring for Contract Data Annotation jobs? Cities in California with the most Contract Data Annotation job openings:
Infographic showing various Contract Data Annotation job openings in California as of July 2026, with employment types broken down into 3% Locum Tenens, 42% Full Time, 35% Part Time, 2% Contract, 17% Nights, and 1% Summer. Highlights an 56% Physical, 1% Hybrid, and 43% Remote job distribution.
Data Annotation Specialist

Data Annotation Specialist

Blackstone Talent Group

San Mateo, CA • On-site

$30 - $35/hr

Other

Posted 11 days ago


Job description

Data Annotation Specialist


Position Details:

Location: San Francisco, CA 94107 (Onsite)

Type: Contract

$30-35w2 per hour


The Annotation QA Specialist is responsible for ensuring the quality, accuracy, and consistency of annotated datasets. Working closely with internal teams, this role maintains high standards of data integrity and supports the smooth execution of data-related projects.


Responsibilities

  • Serve as the primary quality checkpoint for our route configuration and annotation process, ensuring adherence to quality standards and project requirements.
  • Review and evaluate datasets for accuracy, completeness, and consistency — identifying, flagging, and resolving discrepancies or errors.
  • Conduct regular quality control audits on annotated data, implementing and tracking corrective measures as needed.
  • Document QA findings and trends, providing actionable insights and recommendations to improve annotation quality over time.
  • Collaborate with annotation team members and cross-functional partners to communicate quality standards and address recurring issues.
  • Assist with data analysis and reporting tasks as needed.


Required Qualifications

  • Excellent attention to detail with a high degree of accuracy in reviewing and evaluating annotated data.
  • Strong communication and interpersonal skills, with the ability to work effectively in a team environment.
  • Ability to prioritize tasks, meet deadlines, and adapt to shifting project requirements.
  • Strong analytical and problem-solving skills, with the ability to translate data findings into actionable recommendations.
  • Proficiency in spreadsheet tools (Excel, Google Sheets).




EEO Statement:


Blackstone Talent Group is a division of Blackstone Technology Group, a global IT services and solutions firm that implements technological solutions across commercial industry verticals and the US Federal Government. Blackstone’s global talent augmentation practice was founded in 1998. Blackstone Talent Group has offices in San Francisco, Denver, Houston, Colorado Springs, and Washington, DC. We specialize in providing clients the best talent across a variety of industries and sectors.