ZipRecruiter

Log In

1

Data Annotation Manager Jobs in California (NOW HIRING)

Encord

Human Data Solutions Engineer

San Francisco, CA · On-site

$134K - $162K/yr

The role As a Human Data Operations & Solutions Engineer at Encord, you will sit at the ... Manage end-to-end delivery of small-scale annotation POCs -- translating complex AI requirements ...

Encord

Human Data Solutions Engineer

San Francisco, CA · On-site

$134K - $162K/yr

The role As a Human Data Operations & Solutions Engineer at Encord, you will sit at the ... Manage end-to-end delivery of small-scale annotation POCs - translating complex AI requirements ...

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 ...

Figure

Data Quality Partner Lead

San Jose, CA · On-site

$120K - $180K/yr

Direct experience managing data annotation, labeling, or content review vendors * Background at a ... frontier AI lab, autonomous vehicle company, or other organization where data quality at scale was ...

Figure

Data Quality Partner Lead

San Jose, CA

$120K - $180K/yr

Direct experience managing data annotation, labeling, or content review vendors * Background at a ... frontier AI lab, autonomous vehicle company, or other organization where data quality at scale was ...

TSMC

Senior Data Engineer / Data Curator

San Jose, CA · On-site

$124K - $168K/yr

... managing large datasets. • Experience with data annotation tools and platforms for manual or semi-automated labeling. • Experience with NLP data formats, such as JSONL, text, or embeddings, and ...

Figure

Helix AI Engineer, Data Infrastructure

San Jose, CA · On-site

$150K - $350K/yr

Experience building data annotation and dataset management tools. The US base salary range for this full-time position is between $150,000 - $350,000 annually. The pay offered for this position may ...

Mill

AI Engineer, Computer Vision

San Bruno, CA · On-site

Responsibilities : • Build and manage the end-to-end ML training pipeline: data ingestion from deployed kitchen units, ground truth generation, annotation tooling (including foundation-model ...

next page

Showing results 1-20

All 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 2, 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 June 2026, with employment types broken down into 3% As Needed, 53% Full Time, 41% Part Time, and 3% Temporary. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $95,873 per year, or $46.1 per hour.

Technical Project Associate

Abaka AI

Mountain View, CA • On-site

Full-time

Posted 2 hours ago

Job description

Job Summary:
Abaka AI is built on the mission to be the world’s most trusted data partner for AI companies. The Technical Project Associate will help design, build, and scale operational systems for AI data annotation and quality control programs, focusing on automating workflows and improving operational efficiency.
Responsibilities:
• Design, build, improve, and maintain internal workflows, automation systems, and operational tooling for data annotation and quality control programs
• Develop scripts, integrations, and AI-assisted solutions that reduce manual work and improve operational efficiency
• Build and maintain dashboards, reporting systems, and data management workflows that improve visibility across projects
• Collaborate with Project Managers, Operations teams, Reviewers, and Leadership to identify bottlenecks and implement scalable solutions
• Monitor workflow performance, troubleshoot operational issues, and resolve data inconsistencies
• Leverage AI coding agents and AI-assisted development tools to rapidly prototype, test, and deploy process improvements
• Create systems that improve reviewer productivity, quality control accuracy, project tracking, and operational reporting
• Document internal tools, workflows, and best practices to support long-term scalability
• Proactively identify opportunities for automation and operational optimization instead of only executing predefined tasks
• Support cross-functional initiatives as Abaka AI continues to scale globally
Qualifications:
Required:
• Bachelor’s degree in Computer Science, Computer Engineering, Data Engineering, Information Systems, Industrial Engineering, or a related technical field
• Strong technical foundation in software development, automation, systems building, or operational tooling
• Experience improving business or operational processes through automation and tooling development: building projects, scripts, automations, or internal tools using Python or similar programming languages
• Familiarity with AI coding agents and AI-assisted development tools such as Claude Code, Codex, Cursor, GitHub Copilot, or similar platforms
• Understanding of APIs, workflow automation, system integrations, and structured data management concepts
• Familiarity with databases, data modeling, and operational data workflows
• Experience building or maintaining workflows using platforms such as Airtable, Retool, Zapier, n8n, Make, or similar tools
• Strong analytical thinking and problem-solving abilities
• Excellent communication and cross-functional collaboration skills
• Self-motivated, proactive, and comfortable operating in fast-paced, ambiguous environments
• Ability to quickly learn new tools, systems, and operational workflows
Preferred:
• Experience building workflow automation systems, internal operational tools, or reporting dashboards
• Familiarity with cloud infrastructure and developer tools such as AWS, GCP, Docker, Airflow, or similar technologies
• Experience supporting data annotation, AI training, data operations, or quality assurance workflows
• Previous experience as a reviewer, QA/QC specialist, trainer, or operations analyst
• Interest in AI, machine learning, and large-scale data infrastructure
Company:
Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA, with a team of 51-200 employees. The company is currently Growth Stage.

Apply