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Online Data Labelling Jobs (NOW HIRING)

QuinStreet

Data Analyst

Foster City, CA · Remote

$85K - $100K/yr

... online marketplaces that match searchers and "research and compare" consumers with brands ... We run these virtual- and private-label marketplaces in one of the nation's largest media networks.

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Online Data Labelling information

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$46K

$165K

$243.5K

How much do online data labelling jobs pay per year?

As of May 31, 2026, the average yearly pay for online data labelling in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Online Data Labeller, and why are they important?

To excel as an Online Data Labeller, you need strong attention to detail, basic data handling skills, and familiarity with data annotation protocols, often requiring at least a high school diploma. Proficiency with data labelling platforms such as Labelbox, Supervisely, or Scale AI, and sometimes knowledge of spreadsheet tools, is typically necessary. Reliability, consistency, and the ability to follow detailed guidelines make individuals stand out in this role. These skills ensure high-quality, accurately labelled datasets that are critical for training effective AI and machine learning models.

What are some common challenges faced by online data labelers, and how can they be managed effectively?

Online data labelers often encounter challenges such as repetitive tasks, strict accuracy requirements, and tight deadlines. Maintaining high attention to detail is crucial, as even small errors can impact the quality of machine learning models. To manage these challenges, it's helpful to take regular breaks, use productivity tools, and communicate any ambiguities or unclear instructions with supervisors or team leads. Many organizations also offer support channels and quality assurance feedback to help labelers continuously improve their work.

What is online data labelling?

Online data labelling is the process of tagging or annotating data—such as images, text, or audio—using digital tools to make it understandable for machine learning algorithms. Data labelers review raw data and apply predefined labels to help train artificial intelligence systems, enabling them to recognize patterns and make predictions. This work is essential for improving the accuracy and performance of AI models in various applications, such as image recognition, natural language processing, and autonomous vehicles. Online data labelling jobs are often remote and require attention to detail, consistency, and sometimes domain-specific knowledge.

What is the difference between Online Data Labelling vs Data Annotation?

AspectOnline Data LabellingData Annotation
CredentialsBasic computer skills, attention to detailSimilar, often no formal certification required
Work EnvironmentRemote, flexibleRemote or in-office, depending on project
Industry UsageCommon in AI/ML data preparationUsed across AI, computer vision, NLP projects
Search IntentOnline Data Labelling vs Data Annotation

Online Data Labelling and Data Annotation are closely related roles in AI data preparation. While both involve labeling data for machine learning, Online Data Labelling often emphasizes quick, online tasks, whereas Data Annotation may include more detailed, specialized labeling. Both roles are essential in training AI models and share similar skills and work environments.

More about Online Data Labelling jobs
What cities are hiring for Online Data Labelling jobs? Cities with the most Online Data Labelling job openings:
What are the most commonly searched types of Data Labelling jobs? The most popular types of Data Labelling jobs are:
What states have the most Online Data Labelling jobs? States with the most job openings for Online Data Labelling jobs include:
Online Data Labelling jobs near you
Infographic showing various Online Data Labelling job openings in the United States as of May 2026, with employment types broken down into 78% Part Time, and 22% Contract. Highlights an 85% Physical, and 15% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Senior Software Engineer, Auto Labelling

Waabi

San Francisco, CA • On-site, Remote

$170K - $220K/yr

Full-time

Posted 2 days ago

Job description

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.
 
With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai

You will...
- Be part of a team of multidisciplinary Research Scientists and Engineers working on building a cutting-edge offline perception and auto-labelling system leveraging computer vision, and machine learning.
- Manage the end-to-end orchestration of the large-scale auto-labelling training, evaluation and automation eco-system.
- Architect and scale the pipeline to handle large-scale data and user requests using distributed computing frameworks.
- Collaborate with ML researchers and engineers to seamlessly deploy new architectures into the production environment.
Qualifications:
- Bachelors degree with a Computer Science, Robotics and/or similar technical field(s) of study.
- 3+ years of experience developing solutions in ML systems or the ML software stack.
- Deep understanding of ML system architecture, performance analysis, and profiling tools to optimize complex workloads.
- Experience with the end-to-end productionization of deep learning models, particularly large-scale online inference.
- Proficient in Python with a track record of writing high-quality, well-structured, and well-tested "production-grade" code.
- Open-minded and collaborative team player with the willingness to help others.
 
Bonus/nice to have:
- Familiarity with 3D data (LIDAR/Point Clouds) and multi-modal sensor fusion perception models.
- Experience working with large Vision-Language Models (VLMs)
The US yearly salary range for this role is: $170,000 - $220,000 USD in addition to competitive perks & benefits. Waabi (US) Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.

Perks/Benefits:
- Competitive compensation and equity awards.
- Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).
- Unlimited Vacation.
- Flexible hours and Work from Home support.
- Daily drinks, snacks and catered meals (when in office).
- Regularly scheduled team building activities and social events both on-site, off-site & virtually.
- As we grow, this list continues to evolve! 
 
Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact!
 
Waabi is an equal opportunity employer. We celebrate diversity and are committed to creating a supportive, inclusive, and accessible workplace for all our employees. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, age, citizenship, religion, sex, sexual orientation, gender identity or expression, military or veteran status, marital status, pregnancy or parental status, caregiver status, disability, or any other characteristic protected by law. We make workplace accommodations for qualified individuals with disabilities as required by applicable law. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. 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.