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Data Annotation Jobs in San Ramon, CA (NOW HIRING)

You'll design and build native Android applications that bring Figure's AI training and data-annotation tooling directly into the hands of robot operators and annotators on the floor - where a web ...

You'll design and build native Android applications that bring Figure's AI training and data-annotation tooling directly into the hands of robot operators and annotators on the floor - where a web ...

... annotation, curation, and quality review • Build and improve QA processes to ensure data output meets the standards required by frontier AI labs • Own product ops for the data platform. Work with ...

Technical Program Manager, Data

San Francisco, CA · On-site

$152K - $196K/yr

They are seeking a Senior Technical Program Manager to lead their data collection and annotation initiatives, ensuring the delivery of high-quality data while collaborating with research and product ...

Lead audio data collection and annotation efforts at Sesame. * Collaborate with research and product teams to understand and formalize their requirements. * Identify and manage internal resources and ...

Data Operations Engineer

San Francisco, CA · On-site

$81K - $110K/yr

Build and maintain internal tooling for labelers, including annotation interfaces, task pipelines, and dataset browsers * Define and enforce quality control standards across all labeled data ...

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Data Annotation information

What does a typical workday look like for someone in a Data Annotation role?

A typical workday as a Data Annotator involves reviewing datasets—such as images, audio, text, or video—and accurately labeling or categorizing information according to specific project guidelines. Most Data Annotators work independently, but they often collaborate with project managers or data scientists to clarify requirements and resolve ambiguities. Tasks may be repetitive, but adhering to precise standards is vital for maintaining data quality. Work environments can range from technology companies to remote or freelance settings, and advancement opportunities exist as team leads or quality assurance specialists for those who excel in consistency and reliability.

Is data annotation a genuine job?

Data annotation is a legitimate job that involves labeling data such as images, text, or audio to help train machine learning models. It often requires attention to detail and familiarity with annotation tools, and can be found in various industries like technology and healthcare.

Does data annotation pay well?

Data annotation jobs typically offer entry-level pay that varies depending on the employer, location, and complexity of the tasks. While some positions pay hourly wages comparable to other administrative or clerical roles, experienced annotators working on specialized projects or with advanced tools can earn higher rates. Overall, data annotation is often considered an entry-level position with moderate pay potential.

What is a Data Annotation job?

A Data Annotation job involves labeling and categorizing data, such as text, images, audio, or video, to help train machine learning models. Annotators apply tags, bounding boxes, or classifications to data based on specific guidelines. This process improves the accuracy of AI systems in recognizing patterns and making predictions. Many data annotation jobs require attention to detail and familiarity with specific domains. It is commonly used in applications like autonomous driving, natural language processing, and computer vision.

How hard is it to get hired by data annotation?

Getting hired for a data annotation role generally requires basic computer skills, attention to detail, and sometimes familiarity with specific 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 are the key skills and qualifications needed to thrive in the Data Annotation position, and why are they important?

To thrive in Data Annotation, you need strong attention to detail, accuracy, and basic data handling skills, often supported by a high school diploma or equivalent. Familiarity with annotation platforms, data labeling software, or content management systems is frequently required, though specific certifications are rare. Excellent communication, time management, and the ability to focus on repetitive tasks distinguish top performers in this role. These skills are crucial because accurate and consistent data annotation directly impacts the quality of machine learning models and AI applications.

What does a data annotator do?

A data annotator labels and tags data such as images, text, or videos to help machine learning models understand and learn from the data. They use tools and follow guidelines to ensure accuracy and consistency, often working with large datasets in a structured environment. Attention to detail and knowledge of annotation tools are important for this role.
What are popular job titles related to Data Annotation jobs in San Ramon, CA? For Data Annotation jobs in San Ramon, CA, the most frequently searched job titles are:
What job categories do people searching Data Annotation jobs in San Ramon, CA look for? The top searched job categories for Data Annotation jobs in San Ramon, CA are:
What cities near San Ramon, CA are hiring for Data Annotation jobs? Cities near San Ramon, CA with the most Data Annotation job openings:
Infographic showing various Data Annotation job openings in San Ramon, CA as of July 2026, with employment types broken down into 2% Locum Tenens, 35% Full Time, 25% Part Time, 2% Contract, 35% Nights, and 1% Summer. Highlights an 56% Physical, 1% Hybrid, and 43% Remote job distribution.
Annotation QA Specialist

Annotation QA Specialist

Blackstone Talent Group

San Jose, CA • On-site

$30 - $35/hr

Other

Posted 4 days ago

New


Job description

Data Annotation Specialist


Position Details:

Location: San Francisco, CA 94107 (Onsite)

Type: Contract

$30-35w2 per hour

Onsite final interview is required


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.