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Day Data Annotation Jobs (NOW HIRING)

Figure

Data Quality Partner Lead

San Jose, CA · On-site

$120K - $180K/yr

We are based in San Jose, CA and require 5 days/week in-office collaboration. We are looking for a Data Quality Partner Lead to build Figure's external annotation and review vendor network from ...

Figure

Data Quality Partner Lead

San Jose, CA · On-site

$120K - $180K/yr

We are based in San Jose, CA and require 5 days/week in-office collaboration. We are looking for a Data Quality Partner Lead to build Figure's external annotation and review vendor network from ...

RWS Group

$120K - $140K/yr

Oversee complex workstreams including annotation, labeling, linguistic validation, data operations ... Generous paid time off package, starting at 25 days per year (10 sick and 15 vacation), plus ...

RWS Group

$120K - $140K/yr

Oversee complex workstreams including annotation, labeling, linguistic validation, data operations ... Generous paid time off package, starting at 25 days per year (10 sick and 15 vacation), plus ...

RWS Group

Program Manager - Train AI Data Services

$120K - $140K/yr

Oversee complex workstreams including annotation, labeling, linguistic validation, data operations ... Generous paid time off package, starting at 25 days per year (10 sick and 15 vacation), plus ...

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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.
More about Day Data Annotation jobs
What cities are hiring for Day Data Annotation jobs? Cities with the most Day Data Annotation job openings:
What are the most commonly searched types of Data Annotation jobs? The most popular types of Data Annotation jobs are:
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What job categories do people searching Day Data Annotation jobs look for? The top searched job categories for Day Data Annotation jobs are:
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.

Robotics Data Collection Engineer

Nastech Global

Warren, MI • On-site

Contractor

Posted 25 days ago

Job description

Position: Robotics Data Collection Engineer

Location: Warren, Michigan (Onsite)

Duration: 12+Months with possible extensions

Main Skills: Senior Robotics Data Collection Engineer (MLE, Python, Cloud exp, Linux)

Position Summary:

Join Automation, Robotics & Controls (ARC) AI team as a Robotics Data Collection Engineer. In this hands-on role, you will work directly with advanced robotic systems to collect, organize, and validate training data that enables AI-powered robotic manipulation in automotive manufacturing. You will contribute to building the datasets that power the next generation of intelligent manufacturing automation at Warren Technical Center.

Key Responsibilities:

  • Collect high-quality robot telemetry, sensor, and visual data from manufacturing robotic systems in lab and production-like environments.
  • Operate and monitor robotic systems, GELLO teleop interfaces, and data collection hardware.
  • Organize, label, and validate data according to established annotation guidelines and quality standards.
  • Perform manual annotation and verification when necessary to generate high-quality ground truth labels.
  • Execute data collection campaigns following documented protocols and experimental designs.
  • Troubleshoot data collection issues and document problems for engineering teams.
  • Collaborate with AI engineers, robotics engineers, and manufacturing teams to ensure data meets model training requirements.

Required Qualifications:

  • College or bachelor’s degree in engineering (Mechanical Engineering or Electrical Engineering preferred).
  • Ability to work on-site at Warren Technical Center, 5 days per week.
  • Attention to detail and ability to follow technical procedures and documentation.
  • Reliability, accountability, and ability to work independently and as part of a team.
  • Strong, demonstrated hands-on experience operating, troubleshooting, and maintaining industrial or collaborative robotic arms.
  • Proficiency in Linux environments and basic scripting (e.g., Python) to interface with robotic systems and manage data pipelines.
  • Proven experience working directly with perception sensors and hardware, with a solid understanding of capturing and validating high-quality sensor data.

Preferred Qualifications:

  • Experience with robotics, manufacturing, or data collection.
  • Familiarity with Python, Linux, or data tools (beneficial but not required).
  • Experience operating or troubleshooting technical equipment.
  • Basic understanding of machine learning, AI, or data annotation concepts.
  • Experience in automotive or manufacturing environments.

What is Offered:

•              Hands-on experience with cutting-edge robotics and AI technology.

•              Opportunity to contribute to transformative manufacturing automation.

•              Collaborative team environment with world-class engineers and researchers.