ZipRecruiter

Log In

1

Data Annotation Intern Jobs (NOW HIRING)

Alignerr

Machine Learning Engineer

Seattle, WA · Remote

Prior experience with data annotation, data quality assurance, or AI evaluation workflows * Familiarity with large language models (LLMs) and how they are trained or fine-tuned * Background in ...

Labelbox

Applied Research Intern

San Francisco, CA · On-site

Advanced annotation tools, workflow automation, and quality control systems that enable teams to ... Frontier Data Labeling Service : Specialized data labeling through Alignerr, leveraging subject ...

Trunk Tools

MBA/BS Intern - Vision AI

Redmond, WA

$45/hr

About Job MBA/BS Intern - Vision AI Role Overview We are seeking a highly motivated MBA/BS Intern ... Hands-on experience with large-scale data processing and annotation workflows for the construction ...

Tt

AI & Computer Vision Intern

New York, NY

Programming and data tools: Python and/or MATLAB for simple data manipulation, visualization, and ... Labeling platforms: experience with image or point cloud annotation tools (e.g., Supervisely, CVAT ...

next page

Showing results 1-20

People also search for

All JobsData Annotation Intern Jobs

Data Annotation Intern information

See salary details

$12

$22

$42

How much do data annotation intern jobs pay per hour?

As of Jun 3, 2026, the average hourly pay for data annotation intern 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 key skills and qualifications needed to thrive as a Data Annotation Intern, and why are they important?

To thrive as a Data Annotation Intern, you need strong attention to detail, basic computer literacy, and familiarity with data labeling concepts, often supported by a background in computer science or related fields. Familiarity with annotation tools like Labelbox, Supervisely, or CVAT and understanding of data formats such as JSON or XML are typically required. Effective communication, time management, and the ability to follow complex guidelines are important soft skills for this role. These skills ensure high-quality, consistent data labeling, which is crucial for training accurate machine learning models.

What are some common challenges faced by Data Annotation Interns and how can they be overcome?

Data Annotation Interns often encounter challenges such as maintaining consistency and accuracy when labeling large volumes of data, especially when guidelines evolve or when dealing with ambiguous cases. To overcome these challenges, it's important to frequently review annotation guidelines, communicate proactively with supervisors or team members for clarification, and participate in regular quality checks. Collaborating with experienced annotators and leveraging feedback provided during peer reviews can also help interns improve their accuracy and efficiency.

What are Data Annotation Interns?

Data Annotation Interns are entry-level professionals who assist in labeling and categorizing data, such as images, audio, or text, to help train machine learning models. Their work is crucial for ensuring that AI systems can accurately interpret and process various types of data. Interns typically use specialized software tools to annotate data according to specific guidelines, and they may also help with data quality checks. This position is ideal for those interested in gaining experience in artificial intelligence, data science, or related fields.

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

AspectData Annotation InternData Labeling Specialist
CredentialsTypically pursuing or recent graduate in related fieldRelevant experience or certifications in data labeling
Work EnvironmentInternship setting, often in tech or AI companiesFull-time or freelance roles in data annotation projects
Industry UsageCommon in tech, AI, and machine learning industriesUsed across similar industries for data preparation
Job FocusLearning and assisting with data annotation tasksPerforming detailed data labeling and quality control

While both roles involve working with data annotation, a Data Annotation Intern is typically a beginner or student gaining experience, whereas a Data Labeling Specialist is a more experienced professional focused on precise data labeling tasks. Interns often work under supervision, while specialists handle independent projects.

More about Data Annotation Intern jobs
What cities are hiring for Data Annotation Intern jobs? Cities with the most Data Annotation Intern job openings:
What are the most commonly searched types of Data Annotation jobs? The most popular types of Data Annotation jobs are:
What states have the most Data Annotation Intern jobs? States with the most job openings for Data Annotation Intern jobs include:
What job categories do people searching Data Annotation Intern jobs look for? The top searched job categories for Data Annotation Intern jobs are:
Data Annotation Intern jobs near you
Infographic showing various Data Annotation Intern job openings in the United States as of May 2026, with employment types broken down into 50% Internship, and 50% Full Time. Highlights an 100% In-person job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

Software Engineer Intern - Machine Learning Workflow

Halo Industries, Inc.

Santa Clara, CA • On-site

Full-time, Internship

Posted 5 days ago

Job description

The Company


Halo Industries has invented a revolutionary technology to replace a decades-old semiconductor material slicing process. Our laser-based technology eliminates waste, improves material cost and performance, and drives advancements in high-growth markets like automotive, telecommunications, and power electronics. Founded in 2014 at Stanford University, Halo secured significant funding in 2024 and is poised for rapid growth, engaging strategic customers and preparing for volume manufacturing.

The Opportunity

We are looking for a Machine Learning Operations Intern to support data preparation, labeling, training workflows, and validation processes for machine learning systems. The role focuses on executing and monitoring existing ML pipelines, organizing datasets, and helping evaluate model performance.

The intern will work with internal tools and workflows using Python and C#, with guidance from experienced engineers. This position is ideal for someone interested in practical machine learning systems and hands-on experience with real-world data workflows.

Responsibilities
  • Label and organize datasets for machine learning workflows.
  • Run and monitor training and validation pipelines.
  • Assist with evaluating model outputs and identifying data quality issues.
  • Use Python and C# tools to support ML-related workflows and automation.
  • Help troubleshoot pipeline failures and data inconsistencies.
  • Document datasets, experiments, and validation results.
  • Collaborate with engineers to improve workflow efficiency and reliability.
What This Role Offers
  • Hands-on experience with real-world machine learning workflows.
  • Exposure to production ML training and validation systems.
  • Experience working with Python and C# in applied engineering environments.

Requirements

Basic Qualifications
  • Currently pursuing or a recent graduate with a Bachelor`s in Software Engineering, Computer Science, Computer Engineering, or related field.
  • Basic programming experience in Python or C#.
  • Experience working with structured workflows and large datasets.
  • Proficiency to debug simple technical issues and follow documented processes.
Preferred Qualifications
  • Currently pursuing or a recent graduate with a Master`s in Software Engineering, Computer Science, Computer Engineering, or related field.
  • Exposure to machine learning concepts or workflows.
  • Familiarity with Git or collaborative development tools.
  • Experience working with datasets, annotation tools, or automation scripts.

Benefits

Salary Range : 20 - 30 USD per hour.