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Data Annotation Research Jobs in California (NOW HIRING)

Sunday Inc

Data Annotation Lead

Redwood City, CA · On-site

This role is about building and leading a world class in-house data annotation team that is able to pivot quickly to any research experiment while delivering on quality, quantity, and variety when it ...

Welocalize, Inc.

Data Labeling Associate

San Diego, CA

$17 - $22/hr

The ideal candidate will have a foundational understanding of machine learning, data annotation ... User Experience Research team. * Implement basic quality control measures and ensure the ...

Specter

Data Operations Engineer

San Francisco, CA · On-site

$81K - $110K/yr

Role: Specter is hiring a data operations engineer to build our research data operation. This ... Build and maintain internal tooling for labelers, including annotation interfaces, task pipelines ...

New

Turing

Client Director, Frontier Data - US

Palo Alto, CA

$255K - $325K/yr

Oversee the entire data lifecycle from client intake and annotation workflow design to delivery * Partner with product, research, and engineering teams to implement evaluation metrics (e.g., win rate ...

Sesame

Technical Program Manager, Data

San Francisco, CA · On-site

$200K - $260K/yr

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 ...

campus4tech

Technical Program Manager III

Mountain View, CA · On-site

$152K - $197K/yr

The Client's R&D Operations Organization is seeking a highly motivated and technically skilled Technical Program Manager (TPM) to lead and oversee data annotation programs that power our cutting-edge ...

Mercor

Chief Data Scientist

San Francisco, CA · Remote

$70 - $100/hr

Guide research and engineering teams on data science methodology , statistical inference , and ... Prior experience with data annotation , labeling, evaluation, or human feedback collection.

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All JobsData Annotation Research JobsData Annotation Research Jobs in California

Data Annotation Research information

What qualifications do I need for data annotation?

Data annotation research roles typically require basic computer skills, attention to detail, and familiarity with annotation tools or platforms. A high school diploma or equivalent is usually sufficient, though some positions may prefer experience with data labeling, machine learning concepts, or specific software. Strong communication skills and the ability to work independently are also beneficial.

What are some common challenges faced in Data Annotation Research roles, and how can they be addressed?

Professionals in Data Annotation Research often encounter challenges such as maintaining consistency in labeling, dealing with ambiguous data, and managing large datasets efficiently. These issues can be addressed by following detailed annotation guidelines, participating in regular calibration sessions with the team, and utilizing annotation tools that support quality control checks. Collaboration with data scientists and project managers is essential to clarify ambiguities and ensure that annotated data meets the project's requirements. Staying proactive in communication and continuous learning helps to minimize errors and improve overall data quality.

Does data annotation actually pay?

Data annotation research jobs typically pay hourly or per task rates, with wages ranging from minimum wage to higher rates depending on experience and complexity of the work. Many positions are freelance or remote, requiring basic skills in data labeling tools and attention to detail. Payment is generally reliable, but rates vary by employer and project.

How hard is it to get hired by data annotation?

Getting hired for a data annotation research role 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 for those with the right skills and reliability.

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

AspectData Annotation ResearchData Labeling Specialist
CredentialsTypically requires a background in data science, research methods, or related fieldsOften requires basic technical skills and experience with labeling tools
Work EnvironmentResearch labs, tech companies, or remote research teamsData centers, tech companies, or remote labeling teams
Industry UsageUsed in AI/ML research, developing annotation methodologiesUsed in preparing datasets for machine learning models
Search & Comparison IntentUnderstanding research-focused roles in data annotationLooking for practical data labeling jobs

Data Annotation Research involves exploring new annotation techniques and improving data quality for AI models, often requiring research skills. In contrast, Data Labeling Specialists focus on applying existing labeling tools to annotate datasets efficiently. Both roles are essential in AI development but differ in scope and expertise.

Is data annotation real or fake?

Data annotation is a real and essential process in machine learning and AI development, involving labeling data such as images, text, or audio to train algorithms. Data annotation jobs require attention to detail and often use tools like labeling platforms or software, making them a legitimate employment opportunity in the tech industry.

What is data annotation research?

Data annotation research involves studying and developing methods for labeling data, such as images, text, or audio, to be used in training machine learning models. Researchers in this field focus on improving annotation accuracy, efficiency, and scalability, as well as addressing challenges like bias and consistency. This work is critical because high-quality annotated data is essential for building effective AI systems. Data annotation research often includes exploring new tools, techniques, and guidelines for human annotators or automated labeling systems.

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

To thrive as a Data Annotation Researcher, you need strong attention to detail, analytical thinking, and familiarity with data labeling concepts, often supported by a degree in computer science, linguistics, or a related field. Experience with annotation platforms, data management tools, and sometimes knowledge of programming languages like Python are typically required. Excellent communication, problem-solving abilities, and the capacity to work independently set standout contributors apart. These skills ensure high-quality, accurate data labeling, which is crucial for developing reliable AI and machine learning models.
What are popular job titles related to Data Annotation Research jobs in California? For Data Annotation Research jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Annotation Research jobs in California look for? The top searched job categories for Data Annotation Research jobs in California are:
What cities in California are hiring for Data Annotation Research jobs? Cities in California with the most Data Annotation Research job openings:
Data Annotation Research jobs near you
Infographic showing various Data Annotation Research job openings in California as of June 2026, with employment types broken down into 3% As Needed, 11% Full Time, 66% Part Time, 3% Temporary, 15% Contract, and 2% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Data Annotation Lead

Data Annotation Lead

Sunday Inc

Redwood City, CA • On-site

Full-time

Posted 28 days ago

Job description

Join Us in Building the Future of Home Robotics
At Sunday, we're developing personal robots to reclaim the hours lost to repetitive tasks. We're focused on an ambitious goal to make generalized robots broadly accessible, enabling households to take back quality time.
We have spent the last 18 months building a talented team, securing capital, and validating our technology. We are now seeking passionate individuals to join us in the next phase of our growth. If you are ready to apply your skills to the forefront of robotics innovation, we'd love to hear from you.
What to Expect
We're looking for a Data Annotations Lead to join our Data team and own the people side of data annotation.
This role is about building and leading a world class in-house data annotation team that is able to pivot quickly to any research experiment while delivering on quality, quantity, and variety when it comes to data.
You'll work in coordination with Machine Learning, Software engineering, and Data to define the framework and tools on which to build a data annotation team around. Your role is vital to ensuring our data annotators are aligned with the guidances for annotations and are upholding a culture of happiness.
What You'll Do
  • Build a data annotation team
  • Manage the people side of data annotations
  • Create documentation
  • Be in the weeds and annotate data yourself anytime something new is being designed
  • Create data annotation processes
  • Vibe code data annotation tools during pilot stages

What You'll Bring
  • Clear written and verbal communication to guide our data annotators
  • Your ability to manage unexpected challenges
  • Your ownership of key stakeholders with data annotators, engineering, and support
  • Excitement for the growth and development of data annotation
  • Someone adept at prioritization of competing requests, who's able to move both quickly, and in an organized manner
  • A level of hardcore-ness while still treating people like people
  • Intermediate level understanding of ML

Nice to Have
  • Previous experience leading data annotation teams
  • Technical skills to build tools for data annotation
  • Ability to leverage AI to help improve productivity

At Sunday Robotics, we're building technology shaped by real people - curious, creative, and diverse. We're proud to be an equal opportunity employer and consider all qualified applicants regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Even if you don't meet every single requirement, we encourage you to apply. Studies show that women and underrepresented groups often hold back unless they meet 100% of the criteria - we don't want that to be the reason we miss out on great talent.

Apply