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Entry Level Ai Data Annotation Jobs (NOW HIRING)

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 ...

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 ...

Q ANALYSTS LLC

Data Annotation Technician

Kirkland, WA · On-site +1

... AI) and machine learning (ML). Q Analysts is headquartered in San Jose, CA with a presence ... Q Analysts is looking for Data Annotation Technicians to support Ground Truth Data Collection ...

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Entry Level Ai Data Annotation information

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How much do entry level ai data annotation jobs pay per hour?

As of Jun 11, 2026, the average hourly pay for entry level ai data annotation in the United States is $20.24, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $21.88 per hour, depending on experience, location, and employer.

What is an Entry Level AI Data Annotation job?

An Entry Level AI Data Annotation job involves labeling and categorizing data such as images, text, audio, or video to help train artificial intelligence (AI) and machine learning models. Annotators follow specific guidelines to tag data accurately, ensuring that AI systems learn to recognize patterns correctly. These positions typically require attention to detail, basic computer skills, and the ability to follow instructions. No advanced technical knowledge is usually required, making it a great way to start a career in the AI or tech industry.

How much do AI data annotators make?

AI data annotators typically earn between $12 and $20 per hour, depending on experience, location, and the complexity of the annotation tasks. Entry-level positions often pay closer to the lower end of this range, and some roles may offer project-based or part-time pay structures.

What are some common challenges faced by entry-level AI data annotation specialists, and how can they be addressed?

Entry-level AI data annotation specialists often encounter challenges such as maintaining consistency and accuracy while labeling large volumes of data, understanding nuanced instructions, and adapting to changing project requirements. These challenges can be addressed by actively seeking clarification from team leads, participating in training sessions, and regularly reviewing annotation guidelines. Collaborating with teammates and using quality assurance feedback also helps improve accuracy and ensures alignment with project standards.

Can I get an AI job with no experience?

Entry level AI data annotation roles typically do not require prior experience, as they focus on labeling data to train AI models. Basic computer skills, attention to detail, and familiarity with annotation tools are often sufficient to start. Gaining knowledge of AI concepts or tools can improve job prospects but is not always mandatory for entry-level positions.

Can I do data annotation with no experience?

Entry level AI data annotation jobs typically do not require prior experience, as training is often provided to teach specific tools and guidelines. Basic computer skills and attention to detail are usually sufficient to start, making it accessible for beginners. Developing familiarity with annotation tools and understanding data labeling standards can improve job performance and opportunities for advancement.

How to become an AI data annotator?

To become an AI data annotator, you typically need strong attention to detail, basic computer skills, and familiarity with annotation tools or platforms. Many roles are entry-level and may require a high school diploma or equivalent, with some positions offering training. Developing skills in data labeling, understanding of AI concepts, and the ability to work efficiently can improve job prospects.

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

To thrive as an Entry Level AI Data Annotation Specialist, attention to detail, basic computer literacy, and a high school diploma or equivalent are typically required. Familiarity with data labeling platforms, annotation tools, and spreadsheet software is often expected. Strong organizational skills, focus, and the ability to work independently help individuals excel in this role. These skills ensure accurate and efficient data labeling, which is crucial for developing reliable AI and machine learning models.
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Entry Level Ai Data Annotation jobs near you
Infographic showing various Entry Level Ai Data Annotation job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 94% Full Time, 4% Part Time, and 1% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $42,098 per year, or $20.2 per hour.

Data Annotation Specialist

Bot Auto

Houston, TX

Other

Posted 20 days ago

Job description

Company Introduction

At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a startup and the wisdom of seasoned experts, our team has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create groundbreaking solutions that propel the future of transportation. Join us and transform your ideas into reality.

Role Overview

We are seeking a highly meticulous and motivated Data Annotation Specialist to join our team. High-quality data is the lifeblood of our "Physical AI" and the foundation of our autonomous driving system. In this role, you will be responsible for creating, refining, and validating the ground-truth data that powers our perception and mapping stacks. You will work directly with our engineering teams to ensure our models are trained on high-fidelity, ground-truth data that meets our rigorous safety standards.

Key Responsibilities
  • 3D Perception Annotations: Perform high-precision 3D instance labeling, semantic segmentation, and bounding box annotation on multi-sensor data (LiDAR, Camera, Radar, etc.).
  • Vectorized Map Annotation: Annotate and edit high-definition vectorized map elements, including lane geometries, traffic signals, and regulatory features.
  • Human-in-the-Loop Refinement: Examine and refine autolabeling results, identifying edge cases where automated systems may falter.
  • Quality Assurance: Review auto-generated labels against strict pass/fail criteria to ensure only the highest quality data enters our training pipelines.
  • Cross-Functional Feedback: Collaborate closely with Machine Learning and Mapping engineers to provide feedback on labeling guidelines and tool improvements.
  • Documentation: Assist in maintaining clear and concise labeling SOPs (Standard Operating Procedures) to ensure consistency across the data operations team.
Required Qualifications
  • Extreme Attention to Detail: A proven track record of identifying small discrepancies in complex datasets or visual environments.
  • Communication Skills: Outstanding verbal and written communication abilities; ability to clearly explain complex visual scenarios to technical teams.
  • Technical Aptitude: Comfortable working with proprietary software tools and navigating 3D environments (Point Clouds/Bird's Eye View).
  • Adaptability: Ability to thrive in a fast-paced startup environment and pivot between perception and mapping tasks as project priorities shift.
  • Professionalism: High degree of self-discipline and the ability to work independently while meeting rigorous quality and throughput targets.
Preferred Qualifications
  • Prior experience in data annotation for autonomous driving, robotics, or computer vision.
  • Understanding of autonomous vehicle sensor modalities (LiDAR, Radar, Cameras).
  • Experience with 3D labeling tools.
  • Familiarity with HD maps.
Additional Information
  • Onsite Requirement: This position requires being onsite at our Houston, TX 5 days per week.
  • Benefits: Comprehensive benefits with the opportunity to work at the forefront of the autonomous trucking industry.
Why Bot Auto?

We are a small, hyper-focused team on a mission to beat human cost-per-mile through technology. We recently successfully completed the industry's first fully humanless commercial truckload, proving that our vision is a reality. If you are passionate about AI, safety, and transforming logistics, we want to hear from you.

Apply