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Data Annotation Engineer Jobs in San Jose, CA (NOW HIRING)

YO AI Labs

AI Data Scientist Expert - Remote

Palo Alto, CA · Remote

$100 - $200/hr

Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical Documentation * Technical & Report Writing * Content Review & Editing * Data Annotation * Data Interpretation * Fact Checking

YO AI Labs

AI Data Science Expert - Remote

San Jose, CA · Remote

$100 - $200/hr

Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical Documentation * Technical & Report Writing * Content Review & Editing * Data Annotation * Data Interpretation * Fact Checking

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All JobsData Annotation Engineer JobsData Annotation Engineer Jobs in San Jose, CA

Data Annotation Engineer information

See San Jose, CA salary details

$60.4K

$172.8K

$230.9K

How much do data annotation engineer jobs pay per year?

As of Aug 24, 2026, the average yearly pay for data annotation engineer in San Jose, CA is $172,823.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,400.00 and $229,700.00 per year, depending on experience, location, and employer.

What is a data annotation engineer?

A Data Annotation Engineer is responsible for labeling and annotating data—such as text, images, audio, or video—to train machine learning models. They ensure that data is accurately categorized and structured to improve model performance. This role often involves using specialized annotation tools, following detailed guidelines, and working closely with data scientists and AI teams. Data Annotation Engineers play a crucial role in the development of AI applications by providing high-quality labeled datasets for supervised learning.

What are the key skills and qualifications needed to thrive as a data annotation engineer?

To thrive as a Data Annotation Engineer, you need a strong background in data analysis, attention to detail, and familiarity with annotation processes, often supported by a degree in computer science or a related field. Proficiency with annotation tools like Labelbox, CVAT, or VIA, and understanding of data formats used in machine learning, is commonly required. Excellent communication, collaboration, and organizational skills help you effectively manage projects and cooperate with cross-functional teams. These abilities are crucial for delivering high-quality labeled data, which directly impacts the performance of AI and machine learning models.

What are the main challenges faced by data annotation engineers in their daily work?

One of the main challenges Data Annotation Engineers face is ensuring consistent accuracy and quality in labeling large and often complex datasets. Attention to detail is critical, as even small errors can significantly affect machine learning model performance. Additionally, engineers must frequently adapt to evolving annotation guidelines and emerging data types, which requires ongoing learning and flexibility. Collaboration with data scientists and project managers is common to clarify requirements and resolve ambiguities, making strong communication skills essential for success.

What is the salary of data annotation engineer?

The salary of a data annotation engineer typically ranges from $40,000 to $80,000 annually, depending on experience, location, and the complexity of annotation tasks. Entry-level positions may start lower, while experienced professionals with specialized skills in tools like Labelbox or CVAT can earn higher salaries.

What are popular job titles related to Data Annotation Engineer jobs in San Jose, CA?

For Data Annotation Engineer jobs in San Jose, CA, the most frequently searched job titles are:

What job categories do people searching Data Annotation Engineer jobs in San Jose, CA look for?

The top searched job categories for Data Annotation Engineer jobs in San Jose, CA are:

What cities near San Jose, CA are hiring for Data Annotation Engineer jobs?

Cities near San Jose, CA with the most Data Annotation Engineer job openings:

Data Annotation Engineer jobs near you
Infographic showing various Data Annotation Engineer job openings in San Jose, CA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $172,823 per year, or $83.1 per hour.

Operations & Data Annotation Specialist

Avanciers Inc.

Cupertino, CA • On-site

Other

Posted 4 days ago

Job description

Avanciers is a premier IT Staffing/Consulting organization and we are currently recruiting for a Contract role for one of our premier client in USA for Operations & Data Annotation Specialist


Role: Operations & Data Annotation Specialist

Location: Los Angeles, CA / San Diego, CA / Cupertino, CA


Position Summary

The Operations & Data Annotation Specialist will support data annotation and validation workflows by assisting with QA audits, annotation tool configuration, task tracking, test-plan execution, and operational reporting. The role requires strong attention to detail, process compliance, and coordination with cross-functional teams.

Key Responsibilities

  • Support data annotation and validation operations according to defined processes and guidelines.
  • Perform QA audits and review annotation quality for accuracy and consistency.
  • Configure and maintain annotation tools and task workflows.
  • Track annotation tasks, priorities, issues, and completion status.
  • Support test-plan execution and document results, defects, and observations.
  • Prepare operational and quality reports for project stakeholders.
  • Identify process gaps and escalate quality or operational issues.
  • Coordinate with data, QA, engineering, and operations teams to resolve workflow issues.
  • Maintain accurate documentation and ensure compliance with established procedures.

Required Qualifications

  • 2–3 years of experience in data annotation, QA operations, data operations, or a related field.
  • Experience working with annotation or data-labeling tools.
  • Understanding of QA audits, task tracking, and quality processes.
  • Experience supporting test plans and operational reporting.
  • Strong attention to detail and analytical skills.
  • Good communication and stakeholder coordination skills.
  • Ability to work onsite and manage multiple operational priorities.

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