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Full Time Data Annotation Specialist Jobs (NOW HIRING)

Bot Auto

Data Annotation Specialist

Houston, TX · On-site

The Data Annotation Specialist will be responsible for creating, refining, and validating ground-truth data for the company's perception and mapping stacks. Responsibilities : • 3D Perception ...

Bot Auto

Data Annotation Specialist

Houston, TX · On-site

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 ...

Comrise

CA · On-site

$26 - $29/wk

CNC Machinist II - Relocation Packages Available! (Menomonie, WI) Comrise is currently looking for a skilled CNC Machinist II to join our partner's team in Menomonie, WI , to perform intermediate to ...

Encord

Human Data Operations Strategist

San Francisco, CA · On-site

$130K - $210K/yr

You will work closely with cross-functional teams, including clients, annotation specialists, and machine learning engineers, to ensure high-quality data is available for AI models. What you'll do

Encord

Human Data Operations Strategist

San Francisco, CA · On-site

$130K - $210K/yr

You will work closely with cross-functional teams, including clients, annotation specialists, and machine learning engineers, to ensure high-quality data is available for AI models. What you'll do

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Full Time Data Annotation Specialist information

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How much do full time data annotation specialist jobs pay per year?

As of Jul 6, 2026, the average yearly pay for full time data annotation specialist in the United States is $72,947.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,000.00 and $87,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Full Time Data Annotation Specialists, and how can they be managed?

Full Time Data Annotation Specialists often encounter challenges such as maintaining high accuracy while working with large volumes of data, staying focused during repetitive tasks, and adapting to evolving annotation guidelines. Managing these challenges involves developing an eye for detail, regularly reviewing updated instructions, and using productivity techniques like taking short breaks or collaborating with team members to discuss ambiguities. Additionally, many organizations provide ongoing training and support to ensure consistency and quality in annotations.

What is the difference between Full Time Data Annotation Specialist vs Data Labeling Technician?

AspectFull Time Data Annotation SpecialistData Labeling Technician
CredentialsHigh school diploma or equivalent; some roles prefer certifications in data annotationHigh school diploma or equivalent; minimal certifications required
Work EnvironmentOffice or remote; collaborative with data science teamsWarehouse or office; focused on labeling tasks
Industry UsageUsed across AI, machine learning, and data science industriesPrimarily in AI and machine learning sectors for data preparation

The Full Time Data Annotation Specialist and Data Labeling Technician roles both involve preparing data for AI models. The specialist typically has broader responsibilities, may require certifications, and works in collaborative environments, while the technician focuses on specific labeling tasks with minimal credentials. Both roles are essential in the data annotation process within AI industries.

What are the key skills and qualifications needed to thrive as a Full Time Data Annotation Specialist, and why are they important?

To thrive as a Full Time Data Annotation Specialist, you need strong attention to detail, basic data literacy, and familiarity with data labeling concepts, often supported by a high school diploma or higher. Proficiency in using annotation tools (such as Labelbox or Supervisely), spreadsheets, and sometimes basic scripting is typically required. Excellent communication, time management, and the ability to follow detailed instructions help you stand out in this role. These skills and qualities are crucial to ensure high-quality, accurate datasets that drive effective machine learning and AI model development.

What is a Full Time Data Annotation Specialist?

A Full Time Data Annotation Specialist is a professional responsible for labeling and categorizing data, such as images, text, audio, or video, to help train machine learning models. Their primary role involves accurately tagging or marking data according to specific guidelines, which is essential for artificial intelligence and machine learning applications. This job often requires attention to detail, consistency, and sometimes domain-specific knowledge, depending on the project. Data annotation specialists typically work in industries like technology, healthcare, autonomous vehicles, and e-commerce. Full-time positions usually offer stable hours and may include benefits.
More about Full Time Data Annotation Specialist jobs
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Full Time Data Annotation Specialist jobs near you
Infographic showing various Full Time Data Annotation Specialist job openings in the United States as of July 2026, with employment types broken down into 2% Locum Tenens, 19% Full Time, 17% Part Time, 19% Contract, 42% Nights, and 1% Summer. Highlights an 34% Physical, and 66% Remote job distribution, with an average salary of $72,947 per year, or $35.1 per hour.

Data Annotation Specialist

Bot Auto

Houston, TX • On-site

Full-time

Posted 15 days ago

Job description

Job Summary:
Bot Auto is revolutionizing the transportation of goods with autonomous trucks. The Data Annotation Specialist will be responsible for creating, refining, and validating ground-truth data for the company's perception and mapping stacks.
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.
Qualifications:
Required:
• 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:
• 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.
Company:
Transforming American Transportation with Autonomous Trucks Founded in 2023, the company is headquartered in Houston, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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