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Annotation Labelling Jobs (NOW HIRING)

BC Forward

AI Data Annotation Specialist

Charlotte, NC · On-site

$56.08/hr

Create labels for query classification, intent detection, entity and time extraction, metric ... Follow detailed annotation specifications and operational procedures; document decisions, edge ...

Figure

Data Quality Partner Lead

San Jose, CA

$120K - $180K/yr

Direct experience managing data annotation, labeling, or content review vendors * Background at a frontier AI lab, autonomous vehicle company, or other organization where data quality at scale was a ...

Mercor

Network Engineer - Data Annotation

New York, NY · Remote

$50 - $70/hr

Position: Network Engineer - Data for Autonomous Systems annotation Type: Contract Compensation ... Label and classify key behaviors, issues, and anomalies in network data. * Help define schemas and ...

Figure

Data Quality Partner Lead

San Jose, CA · On-site

$120K - $180K/yr

Direct experience managing data annotation, labeling, or content review vendors * Background at a frontier AI lab, autonomous vehicle company, or other organization where data quality at scale was a ...

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Annotation Labelling information

What is annotation labelling?

Annotation labelling is the process of tagging or marking data—such as images, text, or audio—with relevant information or labels. This is an essential step in preparing datasets for machine learning and artificial intelligence models, as it helps algorithms understand and learn from raw data. Annotation labelling can include tasks like identifying objects in photos, transcribing speech, or categorizing text. Skilled annotators ensure accuracy and consistency to improve model performance. People in this role often use specialized tools or software to streamline and standardize the annotation process.

What are the key skills and qualifications needed to thrive as an Annotation Labelling Specialist, and why are they important?

To thrive as an Annotation Labelling Specialist, you need strong attention to detail, data analysis capabilities, and familiarity with data annotation standards, usually supported by a background in computer science or related fields. Proficiency with annotation tools such as Labelbox, CVAT, or Supervisely, and sometimes knowledge of basic programming or scripting, is typically required. Excellent communication, consistency, and the ability to follow complex instructions are crucial soft skills for producing high-quality labeled data. These skills ensure the accuracy and reliability of datasets, which are foundational for successful machine learning and AI model development.

What are some common challenges faced by Annotation Labelling professionals, and how can they be managed?

Annotation Labelling professionals often encounter challenges such as maintaining high accuracy while handling repetitive data, meeting tight deadlines, and adapting to evolving project guidelines. To manage these, it’s important to develop strong attention to detail, regularly communicate with team leads to clarify instructions, and leverage annotation tools efficiently. Collaborating closely with quality assurance teams can also help identify and correct errors early, ensuring consistently high-quality outputs.

What is the difference between Annotation Labelling vs Data Labeling Specialist?

AspectAnnotation LabellingData Labeling Specialist
CredentialsBasic technical skills, attention to detailSimilar skills, sometimes additional domain knowledge
Work EnvironmentData annotation platforms, remote or officeData annotation tasks, often remote or in-office
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, healthcare, retail
Search & ComparisonCommonly compared for entry-level data tasksRelated but broader role

Annotation Labelling involves marking data such as images, text, or videos to train AI models. Data Labeling Specialists perform similar tasks but may have a broader scope, including verifying and managing labeled data. Both roles are essential in AI development, often overlapping in skills and work environment, but Annotation Labelling is more focused on the annotation process itself.

More about Annotation Labelling jobs
What cities are hiring for Annotation Labelling jobs? Cities with the most Annotation Labelling job openings:
What states have the most Annotation Labelling jobs? States with the most job openings for Annotation Labelling jobs include:
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Annotation Labelling jobs near you
Infographic showing various Annotation Labelling job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 56% Full Time, 12% Part Time, 1% Temporary, and 30% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution.
Atlas Data Operations Annotation Manager

Atlas Data Operations Annotation Manager

Boston Dynamics

Waltham, MA • On-site

$115K - $140K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 24 days ago

Job description

Boston Dynamics is a world leader in mobile robots, tackling some of the toughest robotics challenges. We combine the principles of dynamic control and balance with sophisticated mechanical designs, cutting-edge electronics, and next-generation software for high-performance robots equipped with perception, navigation, and intelligence.
The Atlas team is focused on advancing machine learning and manipulation capabilities. We are seeking an Annotation Manager to own data quality and annotation operations for Atlas - setting standards, leading the team, and managing the vendor relationships that produce the training data behind Atlas's AI systems. This role spans software quality assurance, data quality strategy, and hands-on operational leadership, and reports to the Atlas Data Operations Associate Director.
Schedule/Working Hours:
  • Monday - Friday: 40 hours per week, regular hours (e.g., 9 AM to 6 PM, with flexibility across both first and second shift as required).

Responsibilities:
Team Leadership & Performance
  • Directly manage a team of Annotation Leads and Annotation QA Leads, providing day-to-day direction, prioritization, coaching, and performance feedback.
  • Serve as the Atlas working team lead for third-party annotation vendors, managing task allocation, performance accountability, and dual-source relationships to optimize cost, quality, and speed.

Annotation Quality & Operations
  • Own data quality end-to-end - defining standards, QA methodologies, and metrics (accuracy, consistency, rework rates, guideline adherence) - and serve as the primary escalation point for edge cases and labeling ambiguities.
  • Write SOPs and technical documentation for the annotation team and vendors; forecast annotation needs across Atlas engineering stakeholders and drive continuous improvement across tooling, workflows, and guidelines.

Required Skills & Experience:
  • Bachelor's degree in a technical field, data science, or cognitive science preferred; proven experience managing teams in a data annotation, data quality, or machine learning data pipeline environment preferred.
  • Prior experience managing business/contractual relations between third-party annotation vendors/labelling service or BPO service providers strongly preferred. Familiarity with ML data pipelines preferred. Exceptional organizational and communication skills required.

The base pay range for this position is between $115,000 to $140,000 annually. Base pay will depend on multiple individualized factors including, but not limited to internal equity, job related knowledge, skills and experience. This range represents a good faith estimate of compensation at the time of posting. Boston Dynamics offers a generous Benefits package including medical, dental vision, 401(k), paid time off and an annual bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer for employment.

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