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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 ...

DYNA Robotics Inc

AI Data Strategist

Redwood City, CA · On-site

$148K - $192K/yr

Instead of running the day-to-day data pipeline, you will define what operations and research ... Exposure to annotation tooling such as Labelbox, Scale, CVAT, Encord, or Voxel51.

FieldAI

Senior Data Operations Engineer

Boston, MA · On-site

$110K - $140K/yr

... to-day collection and annotation. You'll work directly with the Research Operations Partner to scale FAIRI's in-house data function, and you'll set the technical and operational bar the rest of the ...

FieldAI

Senior Data Operations Engineer

Boston, MA · On-site

$110K - $140K/yr

... to-day collection and annotation. You'll work directly with the Research Operations Partner to scale FAIRI's in-house data function, and you'll set the technical and operational bar the rest of the ...

FieldAI

Senior Data Operations Engineer

Boston, MA

$110K - $140K/yr

... to-day collection and annotation. You'll work directly with the Research Operations Partner to scale FAIRI's in-house data function, and you'll set the technical and operational bar the rest of the ...

Genesys

Language Data Specialist - Korean

... day. Language Data Specialist India Role Overview: Drive the quality and intelligence behind ... Identify opportunities to optimize annotation workflows and improve efficiency at scale

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 ...

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All JobsDay Data Annotation Jobs

Day Data Annotation information

What are the key skills and qualifications needed to thrive as a day data annotation specialist?

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 is a day data annotation job?

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.

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.
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:
What states have the most Day Data Annotation jobs? States with the most job openings for Day Data Annotation jobs include:
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.

Lead Generative AI Analyst - English (US)

Welo Data

Santa Clara, CA • Remote

$50/hr

Full-time

Posted 16 days ago

Job description

We're looking for an experienced Lead Generative AI Analyst to join our team. This leadership role is open to both hybrid and remote candidates, with a preference for those who can work in a hybrid capacity from our Santa Clara, CA office. We're looking for someone who enjoys coordinating people, solving operational challenges, and delivering high-quality results in a fast-paced AI environment.

Rather than focusing on individual annotation work, you'll lead the day-to-day execution of AI data operations, partnering with annotators, quality teams, and cross-functional stakeholders to ensure projects are delivered efficiently, consistently, and at the highest quality standards.

If you have a strong background in project management, operations, or leading production teams—and you're excited about working on cutting-edge Generative AI initiatives—this role is for you.

 
What You'll Do
  • Lead the day-to-day operations of a team of multimodal AI annotators and reviewers.
  • Provide people leadership, including coaching, performance management, workload planning, and team development.
  • Drive project execution by balancing quality, delivery timelines, and operational priorities.
  • Own client-facing meetings, providing project updates, discussing risks, action plans, and delivery progress.
  • Serve as the primary point of contact for workflow questions, issue resolution, and project escalations.
  • Monitor team performance, quality metrics, productivity, and project health, identifying opportunities for continuous improvement.
  • Develop and refine annotation guidelines, documentation, and quality standards as projects evolve.
  • Coordinate calibration sessions and quality reviews to ensure consistent decision-making across the team.
  • Partner with cross-functional stakeholders, including Quality, Operations, Product, and Engineering teams, to resolve complex cases and improve workflows.
  • Support onboarding, coaching, and ongoing development of new team members.
  • Identify operational risks early and proactively drive solutions to keep projects on track.
  • Prepare regular reports on project status, quality trends, and key operational metrics.
What We're Looking For
  • 5+ years of experience in AI data operations, data annotation, content quality, Trust & Safety, data labeling, or similar production environments.
  • 3+ years of experience leading teams and managing projects, with ownership of delivery, quality, and operational outcomes.
  • Demonstrated experience managing personnel, priorities, and multiple workstreams simultaneously.
  • Experience leading client meetings and communicating project status to internal and external stakeholders.
  • Strong stakeholder management and communication skills.
  • Excellent written and verbal English.
  • Exceptional organizational skills with the ability to prioritize in a fast-moving environment.
  • Experience creating documentation, operational processes, or quality guidelines.
  • Comfortable making decisions in ambiguous situations while maintaining consistency and accuracy.
Preferred Qualifications
  • Experience leading AI, machine learning, or multimodal annotation programs.
  • Experience managing QA operations, calibration sessions, audits, and quality improvement initiatives.
  • Familiarity with annotation tools and AI data workflows.
  • Experience working with Product, Engineering, Research, or Vendor Management teams.
  • Knowledge of reporting, dashboards, workflow optimization, or process improvement.
  • Basic Python, SQL, or data analysis skills are a plus.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Working at Welo Data

What to expect from working at Welo Data

From Welo Data

About Welo Data, in their own words

From Welo Data

Welo Data is a global AI data services company powering the next generation of AI. We build, annotate, and validate the training datasets that make AI models accurate, safe, and ready for the real world — across languages, cultures, and domains.

Our team of experts spans the globe, combining deep technical knowledge with a human-centered approach. If you want your work to shape how AI understands the world, you'll find your place here.

Diversity and inclusion statement

From Welo Data

Our Strength is derived from Winning Together. Welo Data is unequivocally committed to developing and fostering a workplace and organizational culture that values the diversity of thought and perspective delivered by a diverse global workforce operating within an inclusive organization.