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Annotation Tech Jobs in California (NOW HIRING)

... our technology. We are now seeking passionate individuals to join us in the next phase of our ... Own annotation operations end-to-end * Manage the people side of data annotations * Create ...

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Annotation Tech information

What are Annotation Techs?

Annotation Techs, short for Annotation Technicians, are professionals who label, categorize, and tag data—such as images, text, or audio—to help train machine learning models. Their work is critical in fields like artificial intelligence, where high-quality, accurately labeled data is needed to teach algorithms how to recognize patterns and make decisions. Annotation Techs may use specialized software tools to identify objects in images, transcribe speech, or classify pieces of text. Attention to detail and consistency are key skills in this role, as errors or inconsistencies can affect the performance of AI systems. These professionals often work in teams and may collaborate with data scientists and engineers to ensure data quality.

How hard is it to get hired by data annotation?

Getting hired as an annotation technician typically requires basic computer skills, attention to detail, and sometimes familiarity with annotation tools or platforms. Many positions are entry-level and do not require advanced education, making the hiring process relatively accessible, though competition can vary based on the employer and location.

What is the difference between Annotation Tech vs Data Labeler?

AspectAnnotation TechData Labeler
Required CredentialsHigh school diploma or equivalent; some roles may prefer technical certificationsHigh school diploma or equivalent; minimal certifications needed
Work EnvironmentOffice or remote; using specialized annotation toolsOffice or remote; using basic labeling software
Industry UsageAI, machine learning, autonomous vehicles, healthcareAI, machine learning, data preparation

Annotation Tech and Data Labeler roles often overlap in data preparation for AI projects. Annotation Tech typically involves more specialized tools and may require some technical knowledge, whereas Data Labelers focus on basic labeling tasks. Both roles are essential in training AI systems, but Annotation Tech positions often demand a deeper understanding of annotation processes and tools.

What does an annotation job do?

An annotation job involves labeling or tagging data, such as images, text, or videos, to help train machine learning models. Annotation technicians use specialized tools to add accurate labels, which are essential for developing AI systems, and often require attention to detail and knowledge of data privacy. The work is typically performed in a digital environment with flexible schedules and may require basic technical skills.

What are the key skills and qualifications needed to thrive as an Annotation Tech, and why are they important?

To thrive as an Annotation Tech, you need strong attention to detail, data labeling proficiency, and familiarity with data annotation guidelines, often supported by a background in computer science or related fields. Experience with annotation platforms such as Labelbox, Supervisely, or CVAT, and sometimes knowledge of basic scripting or data formats like JSON and XML, is typically required. Excellent communication, problem-solving skills, and the ability to follow complex instructions set top performers apart. These skills ensure high-quality, accurate data labeling that directly impacts the effectiveness of machine learning models.

Is annotation tech legit?

Annotation tech refers to roles involving labeling and annotating data for machine learning and AI training. These jobs are generally legitimate and often involve tasks like image, text, or audio annotation using specialized tools, with some positions offering flexible schedules and remote work. However, job seekers should verify the employer's reputation and avoid scams by researching the company before applying.

What are some common challenges faced by Annotation Techs when working with large datasets?

Annotation Techs often work with large and diverse datasets, which can present challenges such as maintaining consistency and accuracy across annotations, especially when dealing with ambiguous or complex data. Additionally, the repetitive nature of the work can lead to fatigue, making it important to stay focused and adhere to established guidelines. Collaboration with data scientists and project managers is crucial to clarify requirements and address any uncertainties, ensuring that the annotated data meets project standards and deadlines.

Does data annotation tech really pay?

Data annotation technicians typically earn hourly wages that range from minimum wage to around $15-$20 per hour, depending on experience, location, and the complexity of tasks. Some companies offer bonuses or pay increases for specialized skills or certifications, but overall, pay is generally modest compared to other tech roles.
What are popular job titles related to Annotation Tech jobs in California? For Annotation Tech jobs in California, the most frequently searched job titles are:
What job categories do people searching Annotation Tech jobs in California look for? The top searched job categories for Annotation Tech jobs in California are:
What cities in California are hiring for Annotation Tech jobs? Cities in California with the most Annotation Tech job openings:
Infographic showing various Annotation Tech job openings in California as of July 2026, with employment types broken down into 4% Locum Tenens, 42% Full Time, 35% Part Time, 2% Contract, and 17% Nights. Highlights an 56% Physical, 1% Hybrid, and 43% Remote job distribution.
Data Annotation Specialist

Data Annotation Specialist

Blackstone Talent Group

Santa Clara, CA • On-site

$30 - $35/hr

Other

Posted 7 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.