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Day Data Annotation Jobs (NOW HIRING)

Bot Auto

Data Annotation Specialist

Houston, TX · On-site

Role Overview We are seeking a highly meticulous and motivated Data Annotation Specialist to join ... Onsite Requirement: This position requires being onsite at our Houston, TX 5 days per week.

Encord

Human Data Operations Strategist

San Francisco, CA · On-site

$150K - $230K/yr

Oversee data annotation projects, translating complex AI and machine learning requirements into ... Strong in-person culture: 3-5 days/week in our newly launched North Beach loft office * Flexible ...

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Data Annotator (Autonomous Vehicle / AI)

San Francisco, CA · On-site

$32 - $39/hr

The ideal candidate is detail-oriented, technically proficient in 2D and 3D annotation, and ... Ability to work on-site five days per week * Willingness to meet strict production benchmarks and ...

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All JobsDay Data Annotation Jobs

Day Data Annotation information

Can I use ChatGPT for data annotation?

Day Data Annotation jobs typically involve labeling data manually to improve machine learning models. While ChatGPT can assist with generating or reviewing data, it is not a substitute for the detailed, accurate labeling performed by human annotators required in these roles.

Is it hard to get hired for data annotation?

Getting hired for a data annotation role generally depends on the employer's requirements, such as attention to detail and basic computer skills. Many positions are entry-level and may not require extensive experience or certifications, making them accessible to a wide range of applicants. However, competition can vary based on the company's demand and the complexity of the annotation tasks.

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

To excel as a Day Data Annotation Specialist, you need strong attention to detail, data entry accuracy, and a solid understanding of the subject matter being annotated, often supported by a high school diploma or relevant experience. Familiarity with annotation tools, spreadsheets, and data management software is typically required. Excellent concentration, time management, and clear communication skills help professionals stand out in this role. These abilities are crucial to ensure high-quality, consistent data labeling that directly impacts the performance of machine learning models and downstream business applications.

What are Day Data Annotation jobs?

Day Data Annotation jobs involve reviewing and tagging data, such as images, text, audio, or video, during regular daytime hours. Annotators help prepare datasets for machine learning and artificial intelligence by labeling or categorizing information according to specific guidelines. This work is essential for training algorithms to recognize patterns, objects, or language. Day Data Annotation can be done remotely or in-office, and it often requires attention to detail and good communication skills.

What is the difference between Day Data Annotation vs Data Labeler?

AspectDay Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, collaborative teamsRemote or on-site, independent work
Industry UsageAI/ML companies, tech firmsAI/ML, data processing companies
Job FocusAnnotating data for machine learning modelsLabeling data to train AI systems

Day Data Annotation and Data Labeler roles are similar, focusing on preparing data for AI. Day Data Annotation often involves more detailed annotation tasks, while Data Labelers may perform broader labeling activities. Both roles require basic technical skills and are vital in AI development across tech industries.

Does data annotation really pay you?

Data annotation jobs, including day data annotation roles, typically pay hourly or per task rates, with earnings varying based on experience, complexity of tasks, and platform. Many annotators earn a modest income, often comparable to entry-level work, and consistent pay depends on workload and employer policies.

Is data annotation real or fake?

Data annotation is a legitimate job involving labeling data such as images, text, or audio to train machine learning models. It requires attention to detail and familiarity with annotation tools, and it is widely used in AI development. The work is real and essential for creating accurate AI systems.

What are some common challenges faced by Day Data Annotation specialists and how can they be addressed?

Day Data Annotation specialists often encounter challenges such as maintaining high accuracy while handling repetitive tasks, interpreting ambiguous data, and meeting tight deadlines. To address these, it's important to develop strong attention to detail, use project guidelines as references, and communicate with team leads or peers when uncertainties arise. Many organizations also provide regular feedback and quality assurance checks, which help annotators improve their performance and consistency over time.
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Day Data Annotation jobs near you
Infographic showing various Day Data Annotation job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 60% Full Time, 36% Part Time, 2% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data Annotation Specialist

Bot Auto

Houston, TX • On-site

Other

This job post has expired today. Applications are no longer accepted.

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