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Intern Data Annotation Tech Jobs in California (NOW HIRING)

... our technology. We are now seeking passionate individuals to join us in the next phase of our ... This role is about building and leading a world class in-house data annotation team that is able to ...

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Oversee data annotation projects, translating complex AI and machine learning requirements into ... technology companies * Proven ability to own complex, multi-stakeholder workflows end-to-end ...

Computer Vision Engineer

Palo Alto, CA ยท On-site

$131K - $154K/yr

Computer Vision Intern - Data Labeling & Annotation Type: Temporary Duration: 6 months - 12 months What You'll Gain * Exposure to the full CV pipeline, from raw data to deployed model * Mentorship ...

Computer Vision Engineer

Palo Alto, CA

$131K - $154K/yr

Computer Vision Intern - Data Labeling & Annotation Type: Temporary Duration: 6 months - 12 months What You'll Gain * Exposure to the full CV pipeline, from raw data to deployed model * Mentorship ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

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Intern Data Annotation Tech information

What are some common challenges faced by Intern Data Annotation Techs, and how can they overcome them?

Intern Data Annotation Techs often encounter challenges such as maintaining consistency in labeling large datasets and understanding nuanced instructions for annotation tasks. To overcome these hurdles, it's important to ask clarifying questions early on, regularly review annotation guidelines, and participate in team discussions about edge cases. Collaboration with more experienced annotators and feedback from supervisors also help in refining skills and ensuring high-quality data preparation. Developing attention to detail and adaptability will contribute to a successful internship experience.

What is the difference between Intern Data Annotation Tech vs Intern Data Labeler?

AspectIntern Data Annotation TechIntern Data Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentData annotation platforms, remote or officeData labeling platforms, remote or office
Industry UsageAI, machine learning, data scienceAI, machine learning, data science
Job FocusAnnotating data for training AI modelsLabeling data for machine learning algorithms

Both roles involve preparing data for AI systems, with similar skills and work environments. The main difference lies in terminology; 'Data Annotation Tech' emphasizes technical annotation tasks, while 'Data Labeler' is a more general term. Both are entry-level positions vital for training AI models in the tech industry.

What are Intern Data Annotation Techs?

Intern Data Annotation Techs are entry-level professionals, often students or recent graduates, who support machine learning projects by labeling and categorizing data, such as images, text, or audio. Their work is essential for training AI systems, as accurately annotated data helps algorithms learn to make correct predictions. These interns typically use specialized software tools to tag or classify data according to specific guidelines. The role requires attention to detail, consistency, and sometimes basic technical skills, depending on the complexity of the data and tasks. Internships in data annotation can provide valuable exposure to the fields of artificial intelligence and data science.

What are the key skills and qualifications needed to thrive as an Intern Data Annotation Tech, and why are they important?

To thrive as an Intern Data Annotation Tech, you need attention to detail, basic data management skills, and familiarity with data labeling concepts, often supported by a high school diploma or ongoing college coursework. Experience with annotation platforms, spreadsheet tools, and sometimes basic scripting languages is helpful. Strong communication, reliability, and the ability to follow detailed instructions are valuable soft skills in this role. These abilities ensure accurate and efficient data labeling, which is critical for training reliable machine learning models.
What are the most commonly searched types of Data Annotation Tech jobs in California? The most popular types of Data Annotation Tech jobs in California are:
What are popular job titles related to Intern Data Annotation Tech jobs in California? For Intern Data Annotation Tech jobs in California, the most frequently searched job titles are:
What job categories do people searching Intern Data Annotation Tech jobs in California look for? The top searched job categories for Intern Data Annotation Tech jobs in California are:
What cities in California are hiring for Intern Data Annotation Tech jobs? Cities in California with the most Intern Data Annotation Tech job openings:
Infographic showing various Intern Data Annotation Tech job openings in California as of May 2026, with employment types broken down into 2% Locum Tenens, 44% Full Time, 19% Part Time, 2% Temporary, and 33% Contract. Highlights an 46% Physical, 1% Hybrid, and 53% Remote job distribution.
Data Annotation Lead

Data Annotation Lead

Sunday Inc

Redwood City, CA โ€ข On-site

Full-time

Posted 2 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

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.