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Day Shift Ai Data Annotation Jobs (NOW HIRING)

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Data Annotation Specialist

Houston, TX · On-site

... shift. • Professionalism: High degree of self-discipline and the ability to work independently ... Preferred : • Prior experience in data annotation for autonomous driving, robotics, or computer ...

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Data Annotation Specialist

Houston, TX · On-site

They are seeking a meticulous Data Annotation Specialist responsible for creating, refining, and ... shift. • Professionalism: High degree of self-discipline and the ability to work independently ...

Abaka AI

Data Operations Engineer

Mountain View, CA · On-site

$136.30K - $163.60K/yr

Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA ...

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 ...

Telus Digital

$168K - $210K/yr

Our data annotation capabilities transform raw, ambiguous data into contextually enriched training ... Data & AI Expertise & Solutioning * Develop and maintain deep expertise across TELUS Digital's Data ...

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 ...

Abaka AI

Data Acquisition Engineer

Mountain View, CA · On-site

$136.30K - $163.60K/yr

Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA ...

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Day Shift Ai Data Annotation information

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

To thrive as a Day Shift AI Data Annotation Specialist, you need strong attention to detail, basic computer literacy, and proficiency in following instructions, often supported by a high school diploma or equivalent. Familiarity with annotation platforms, labeling tools, and sometimes simple scripting or spreadsheet software is typically required. Effective communication, time management, and the ability to stay focused during repetitive tasks are valuable soft skills in this role. These capabilities ensure high-quality, accurate data labeling, which is critical for training reliable AI models.

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

Day Shift AI Data Annotation specialists often encounter challenges like maintaining focus and accuracy during repetitive tasks, meeting tight deadlines, and staying consistent with evolving annotation guidelines. To address these, it's helpful to take regular short breaks to reduce fatigue, actively participate in team discussions to clarify guidelines, and use quality assurance tools or peer reviews to ensure data accuracy. Many teams also offer support through continuous training and feedback, which can help annotators improve their skills and efficiency over time.

What are Day Shift AI Data Annotation jobs?

Day Shift AI Data Annotation jobs involve labeling and categorizing data, such as images, text, or audio, during daytime working hours to help train artificial intelligence systems. Annotators review raw data and apply tags or labels according to specific guidelines, ensuring AI models learn to recognize patterns accurately. These roles are essential for improving the quality and reliability of machine learning algorithms. Typically, the work is detail-oriented and may be performed in an office or remotely. Day shift positions appeal to those who prefer standard business hours.

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

AspectDay Shift Ai Data AnnotationData Labeler
CredentialsHigh school diploma or equivalent; basic computer skillsHigh school diploma or equivalent; attention to detail
Work EnvironmentOffice or remote; computer-based tasksOffice or remote; computer-based tasks
Industry UsageAI, machine learning, tech companiesAI, machine learning, tech companies
Job FocusAnnotating data for AI trainingLabeling data for AI models

Both roles involve data annotation and labeling for AI systems, often in similar environments. The main difference lies in terminology; 'Day Shift Ai Data Annotation' emphasizes working during daytime hours, while 'Data Labeler' is a broader term used across various shifts and companies. Both positions require attention to detail and basic technical skills, making them closely related in the AI industry.

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Day Shift Ai Data Annotation jobs near you

Data Annotation Specialist

DYNA Robotics Inc

Redwood City, CA • On-site

Contractor

Posted 25 days ago

Job description

Company Overview:
Dyna Robotics is at the forefront of revolutionizing robotic manipulation with cutting-edge foundation models. Our mission is to empower businesses by automating repetitive, stationary tasks with affordable, intelligent robotic arms. Leveraging the latest advancements in foundation models, we're driving the future of general-purpose robotics-one manipulation skill at a time.
Dyna Robotics was founded by industry leaders who previously achieved a $350 million exit in grocery deep tech as well as top robotics researchers from DeepMind and Nvidia. Our team blends world-class research, engineering, and product innovation to drive the future of robotic manipulation. With $20mil+ in funding, we're positioned to redefine the landscape of robotic automation. Join us to shape the next frontier of AI-driven robotics.
Position Overview:
As a Data Annotation Specialist at Dyna Robotics, you will be pivotal in iterating on our AI system by annotating data on various diverse tasks performed by robots. Your will directly influence the performance of our robotic arms, helping them become more accurate and efficient. You will work closely with our engineering and research teams, ensuring data is labeled of the highest quality and meets required standards.
Key Responsibilities:
  • Manually annotate video sequences (boxes/masks/keypoints), track IDs, and label actions & temporal segments
  • Maintain data integrity by applying guidelines and QC checks; resolve ambiguities and fix errors
  • Leverage pre-annotation/autolabeling tools to boost throughput-validate/correct model prelabels and tune auto-tracking/segmentation pipelines

Qualifications:
  • Associate's or Bachelor's degree (or equivalent experience)
  • Strong attention to detail; consistent application of guidelines
  • Ability to follow detailed instructions and work independently with minimal supervision
  • Clear written communication and a collaborative attitude

Preferred Qualifications:
  • Hands-on experience annotating video (boxes/masks/keypoints, action labels, ID tracking)
  • Proficiency with annotation tools; comfort with pre-annotation/autolabel review and correction
  • Familiarity with QA practices (inter-annotator agreement, spot checks, golden sets)
  • Knowledge of common annotation formats (e.g., COCO, YOLO, MOT/KITTI) and basic video concepts (frame rate, codecs)

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