US Driver's License Image Annotator

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. OpenTrain helps people start and grow work that directly shapes how modern AI systems behave; creating an OpenTrain account is free.

About AI training and this kind of work

AI training (also called data labeling or human feedback work) is the human side of building artificial intelligence. Contributors annotate images, transcribe audio, review model outputs, and more — work that is often remote, flexible, and accessible to people with diverse backgrounds.

• 100% remote: work from anywhere with a computer and internet connection.
• Flexible, part-time opportunities that fit around school, other jobs, or family.
• Many projects need no prior experience; careful, attentive contributors are in demand.

The role

You will annotate key personal and document information on images of US driver's licenses and state IDs crowdsourced from the internet. This dataset will be used to train and improve document understanding and information extraction models for US driver's licenses.

Work is contract, part-time, less than 20 hours per week, fully remote and open worldwide. Labeling is done on images using bounding-box annotations in Label Studio. Pay is hourly with a listed rate of $5/hr and a published range of $1–$7/hr.

• Data type: IMAGE
• Label type: BOUNDING_BOX
• Labeling software: LABEL_STUDIO
• Employment type: Contractor / Part-time
• Workload: Less than 20 hours/week, flexible schedule
• Location: Worldwide (remote)

What you'll do

Carefully review images of US driver's licenses and place bounding-box annotations for specified fields. Accuracy and consistency are essential because these labels train models that extract personal and document data.

• Annotate fields such as jurisdiction_name, credential_type, real_id_indicator, family_name, given_name, middle_name, suffix, date_of_birth, sex, height, weight, eye_color, hair_color, street_address, city, state, zip_code.
• Also label document_number, class, endorsements, restrictions, date_of_issue, date_of_expiration, under_18_until, under_21_until, organ_donor_indicator, veteran_indicator, portrait, ghost_image, signature, and customer_id_number.
• Work inside Label Studio and follow project annotation guidelines to ensure high-quality labels.

Requirements

This is an entry-level role that prioritizes attention to detail and the ability to read and recognize common US document fields.

• Basic familiarity with what a standard US driver's license or state ID looks like.
• Ability to clearly read English text and recognize common US address formats, dates, and document fields.
• Strong attention to detail and accuracy when extracting information from ID images.
• Previous experience with data labeling, document annotation, or image tagging is a plus but not required.
• No specific education, work experience, or background is needed beyond the above.

How it works

Apply through OpenTrain and create a free account. If selected for the project you will receive access to the labeling workspace and project guidelines in Label Studio.

Complete tasks at your own pace within the project schedule, and submit annotations following the provided instructions. Compensation is hourly and paid according to the project's pay schedule.

Who should apply

This role is a good fit for careful, detail-oriented people who can read US-style dates and addresses and who want flexible, remote contract work contributing to cutting-edge AI systems.

• Entry-level contributors welcome.
• Good for people seeking part-time work under 20 hrs/week.
• Worldwide applicants accepted; no specific language requirements listed.