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Internship Ai Data Annotation Jobs (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 ... Ability to leverage AI to help improve productivity At Sunday Robotics, we're building technology ...

BC Forward

AI Data Annotation Specialist

Charlotte, NC · On-site

$65.05/hr

Collaborate with data science and platform teams to deploy scalable AI solutions. Annotate and label datasets to support training, evaluation, and alignment workflows across NLP and retrieval tasks.

GE HealthCare

Data Manager - AI Development

$94K - $141K/yr

Track annotation progress, throughput, and quality metrics. * Maintain annotation dashboards to ensure timely delivery aligned with AI development milestones. 4. Data Governance & Compliance Support

Abaka AI

Technical Project Associate

Mountain View, CA · On-site

Abaka AI is committed to being the world's most trusted data partner for AI companies. The Technical Project Associate will design, build, and scale operational systems for AI data annotation and ...

Q Analysts

Data Annotation Technician

Kirkland, WA · On-site

Data Annotation Technician Join Q Analysts and become part of a world-class organization. Q ... AI) and machine learning (ML). Q Analysts is headquartered in San Jose, CA with a presence ...

Abaka AI

Technical Project Associate

Mountain View, CA · On-site

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 ...

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Internship Ai Data Annotation information

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How much do internship ai data annotation jobs pay per hour?

As of Jul 3, 2026, the average hourly pay for internship ai data annotation in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What are the typical challenges faced during an AI Data Annotation internship, and how can I overcome them?

As an AI Data Annotation intern, you may encounter challenges such as maintaining high accuracy while labeling large volumes of data, understanding complex annotation guidelines, and adapting to evolving project requirements. It's important to regularly communicate with your team lead or project manager to clarify any uncertainties and ensure consistency in your annotations. Leveraging available training materials and asking for feedback will help you improve your efficiency and accuracy, turning these challenges into valuable learning experiences.

What is an AI Data Annotation Internship?

An AI Data Annotation Internship is a temporary position where interns help label, tag, or categorize data (such as images, text, or audio) to train and improve artificial intelligence models. Interns typically work with datasets, ensuring that the information provided is accurate and consistent, which is crucial for machine learning algorithms to learn effectively. The role is a valuable entry point for those interested in AI, machine learning, or data science, as it offers hands-on experience with the foundational work needed to build intelligent systems.

What is the difference between Internship Ai Data Annotation vs Data Labeler?

AspectInternship Ai Data AnnotationData Labeler
CredentialsHigh school diploma or equivalent; some roles prefer basic technical skillsHigh school diploma or equivalent; minimal formal education required
Work EnvironmentOffice or remote; supervised tasks, often part-time or temporaryOffice or remote; repetitive tasks, often entry-level
Industry UsageTech companies, AI startups, research projectsTech firms, data companies, AI development teams
Search & Comparison IntentUnderstanding entry-level roles in AI data annotationComparing entry-level data labeling jobs in AI

Internship Ai Data Annotation roles typically involve supervised, short-term tasks aimed at gaining experience in AI data preparation. Data Labeler positions are similar entry-level roles focused on labeling data for machine learning. Both roles require basic skills and are used across tech and AI industries, but internships often offer more training and learning opportunities.

What are the key skills and qualifications needed to thrive as an Internship AI Data Annotation specialist, and why are they important?

To thrive as an Internship AI Data Annotation specialist, you need attention to detail, basic computer literacy, and a foundational understanding of data labeling concepts, often supported by ongoing training or coursework in data science or computer science. Familiarity with annotation tools like Labelbox, Supervisely, or VIA, and knowledge of data management platforms are commonly required. Strong organizational skills, patience, and effective communication help you manage repetitive tasks and collaborate with team members. These skills are essential to ensure high-quality data labeling, which directly impacts the performance and accuracy of AI models.
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Internship Ai Data Annotation jobs near you
Infographic showing various Internship Ai Data Annotation job openings in the United States as of June 2026, with employment types broken down into 34% Full Time, 64% Part Time, and 2% Temporary. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.
Data Annotation Lead

Data Annotation Lead

Sunday Inc

Redwood City, CA • On-site

Full-time

Posted 26 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