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Data Annotation Manager Jobs in California (NOW HIRING)

Welocalize, Inc.

Data Labeling Associate

San Diego, CA · On-site

$17 - $22/hr

Data Management and Annotation: * Design and develop test and training datasets as per the criteria provided by the project manager and other full-time employees. * Handle data efficiently, ensuring ...

Welocalize, Inc.

Data Quality Analyst

San Francisco, CA · On-site

Data Management and Annotation: * Design and develop test and training datasets as per the criteria provided by the project manager and other full-time employees. * Handle data efficiently, ensuring ...

Figure

Data Quality Partner Lead

San Jose, CA · On-site

They are seeking a Data Quality Partner Lead to build and manage their external annotation and review vendor network from scratch, ensuring high data quality standards are met. Responsibilities : • ...

Turing

Client Director, Frontier Data - US

Palo Alto, CA

$255K - $325K/yr

Demonstrated experience managing dataset generation or annotation for machine learning model evaluation and/or training * Familiarity with ML tools and data workflows (e.g., HuggingFace, LangChain ...

Specter

Data Operations Engineer

San Francisco, CA · On-site

$81K - $110K/yr

Define labeling taxonomies and annotation specifications Qualifications: * 1-3+ years of experience in data operations, project management, or a technical coordination role, ideally supporting ML or ...

Tapestry

Data Science Manager

Mountain View, CA

As a Data Science Manager, you will act as a pivotal technical leader to bridge the gap between ... Annotation Rigor: Drive a comprehensive and scalable data annotation strategy that prioritizes ...

Tapestry

Data Science Manager

Mountain View, CA · On-site

As a Data Science Manager, you will act as a pivotal technical leader to bridge the gap between ... Annotation Rigor: Drive a comprehensive and scalable data annotation strategy that prioritizes ...

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Showing results 1-20

All JobsData Annotation JobsData Annotation Manager JobsData Annotation Manager Jobs in California

Data Annotation Manager information

See California salary details

$30.6K

$95.9K

$169.7K

How much do data annotation manager jobs pay per year?

As of Jul 24, 2026, the average yearly pay for data annotation manager in California is $95,873.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,100.00 and $123,900.00 per year, depending on experience, location, and employer.

What is the salary of data annotation manager?

The salary of a data annotation manager typically ranges from $60,000 to $120,000 annually, depending on experience, location, and company size. Senior roles or those in high-cost areas may offer higher compensation, and familiarity with annotation tools and team management can influence pay levels.

How much do data annotation project managers make?

Data annotation project managers typically earn between $60,000 and $100,000 annually, depending on experience, location, and company size. They oversee annotation teams, coordinate workflows, and ensure quality standards are met, often requiring familiarity with annotation tools and project management skills.

What are some common challenges faced by Data Annotation Managers, and how can they be addressed?

Data Annotation Managers often encounter challenges such as maintaining high annotation quality across large and diverse datasets, managing a distributed team of annotators, and meeting tight project deadlines. To address these, it's important to implement robust quality assurance processes, provide ongoing training for annotators, and establish clear communication channels. Leveraging annotation tools with built-in validation features can also help ensure consistency and accuracy. Building a positive and collaborative team environment further contributes to better outcomes and workflow efficiency.

What does a Data Annotation Manager do?

A Data Annotation Manager oversees the process of labeling and categorizing data used to train machine learning models. They manage teams of annotators, ensure data quality, develop annotation guidelines, and coordinate with data scientists to meet project requirements. Their role is critical in maintaining high standards of accuracy and efficiency, as well as ensuring that datasets are properly prepared for AI and machine learning applications.

Does data annotation actually pay well?

Data annotation managers typically earn competitive salaries that reflect their experience and responsibilities, often ranging from entry-level to senior roles. Compensation can vary based on industry, location, and company size, with specialized skills in tools like labeling platforms and quality control often leading to higher pay.

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

To thrive as a Data Annotation Manager, you need expertise in data labeling processes, quality control, and a solid understanding of machine learning concepts, usually backed by a degree in computer science or a related field. Proficiency with annotation tools such as Labelbox, Supervisely, or CVAT, as well as experience with project management systems, is commonly required. Exceptional leadership, attention to detail, and strong communication skills help manage teams and ensure high annotation accuracy. These skills are critical for delivering reliable labeled datasets, which are essential for building effective AI and machine learning models.

How hard is it to get hired by data annotation?

Getting hired as a data annotation manager typically requires relevant experience in data labeling, familiarity with annotation tools, and strong organizational skills. The hiring process often involves reviewing previous work, technical assessments, and demonstrating attention to detail, with opportunities available in companies that outsource data labeling tasks.

What is the difference between Data Annotation Manager vs Data Labeling Specialist?

AspectData Annotation ManagerData Labeling Specialist
CredentialsBachelor's degree in related field, experience in data managementHigh school diploma or equivalent, training in labeling tools
Work EnvironmentTeam management, project oversight, collaboration with data scientistsHands-on labeling work, using annotation tools, focused on data tagging
Industry UsageUsed in AI/ML projects for overseeing annotation teamsPerforms the actual data labeling tasks in machine learning workflows

The Data Annotation Manager oversees the entire annotation process, managing teams and ensuring quality, while the Data Labeling Specialist focuses on executing labeling tasks. Both roles are essential in AI/ML data preparation but differ in responsibilities and scope.

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 are popular job titles related to Data Annotation Manager jobs in California? For Data Annotation Manager jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Annotation Manager jobs in California look for? The top searched job categories for Data Annotation Manager jobs in California are:
What cities in California are hiring for Data Annotation Manager jobs? Cities in California with the most Data Annotation Manager job openings:
Data Annotation Manager jobs near you
Infographic showing various Data Annotation Manager job openings in California as of July 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 80% In-person, 13% Hybrid, and 7% Remote job distribution, with an average salary of $95,873 per year, or $46.1 per hour.
Data Labeling Associate

Data Labeling Associate

Welocalize, Inc.

San Diego, CA • On-site

$17 - $22/hr

Full-time

Posted 14 days ago

Welocalize rating

6.5

Company rating: 6.5 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

303rd of 454 rated business services

Job description

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Job Responsibilities:

The ideal candidate will have a foundational understanding of machine learning, data annotation, quality assurance, and natural language processing. They will play a pivotal role in updating our machine learning models and ensuring their efficacy.

MAIN TASKS & RESPONSIBILITIES

Machine Learning Model Updates:

  • Update training and test model databases with new or amended synthetic textual and image data.
  • 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 interfaces.
  • Evaluate the performance of trained models to gauge their efficacy and readiness for deployment.

Data Management and Annotation:

  • Design and develop test and training datasets as per the criteria provided by the project manager and other full-time employees.
  • Handle data efficiently, ensuring its integrity throughout the workflow.
  • Engage in data relevance tasks, ensuring data sets are aligned with project goals.
  • Annotate data accurately, ensuring it adheres to set guidelines.

Quality Assurance and Analysis:

  • Conduct manual quality analysis of model results.
  • Recognize error patterns and report anomalies for further investigation.
  • Deliver detailed reports on findings, including aspects such as utterance quality, LLM evaluation, ASR bug tracking, and customer pain points to be reviewed by the User Experience Research team.
  • Implement basic quality control measures and ensure the reliability of processed data.
  • Utilize intermediate data analysis techniques to extract insights and inform decision-making.
  • Arbitrate discrepancies effectively, ensuring consistent data quality.

Linguistic and NLP Tasks:

  • Apply basic knowledge of natural language processing and linguistics to data processing tasks.
  • Ensure linguistic accuracy in all processed and annotated data.

REQUIREMENTS

Preferred Qualifications:

  • Bachelor's degree in Computer Science, Data Science, Linguistics or Computational Linguistics or a related field.

Experience:

  • Ability to work in a fast-paced, collaborative environment.
  • Excellent communication skills

Skills & Knowledge:

  • Familiarity with command-line tools and interfaces.
  • Strong analytical skills with the ability to identify patterns and anomalies.

Additional Information:

This role primarily focuses on English US data sets; however, familiarity with translation or multi-lingual data sets can be a plus for future projects.

Additional Job Details:

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