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Data Annotation Project Manager Jobs in Federal Way, WA

WHAT YOU'LL DO • Execute Data labelling and annotation tasks across speech and voice datasets ... degree holder PROJECT DETAILS • Location: 100% Onsite (Bay Area, Seattle, NYC, or client ...

WHAT YOU'LL DO • Execute Data labelling and annotation tasks across speech and voice datasets ... degree holder PROJECT DETAILS • Location: 100% Onsite (Bay Area, Seattle, NYC, or client ...

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Data Annotation Project Manager information

See Federal Way, WA salary details

$18

$64

$89

How much do data annotation project manager jobs pay per hour?

As of Jul 24, 2026, the average hourly pay for data annotation project manager in Federal Way, WA is $64.22, according to ZipRecruiter salary data. Most workers in this role earn between $55.58 and $75.14 per hour, depending on experience, location, and employer.

How much do data annotation project managers make?

Data annotation project managers typically earn between $60,000 and $100,000 annually, depending on experience, location, and company size. They oversee annotation teams, coordinate workflows, and ensure quality standards using tools like labeling platforms and project management software.

Does data annotation actually pay?

Data annotation project managers oversee tasks where annotators are paid for labeling data used in machine learning. The pay for annotators varies depending on the platform, project complexity, and experience, with many earning hourly wages or per-task rates. The role of a project manager involves coordinating these efforts and ensuring quality, often with a salary or contract-based compensation.

What are the key skills and qualifications needed to thrive as a Data Annotation Project Manager, and why are they important?

To thrive as a Data Annotation Project Manager, you need strong project management skills, a solid understanding of data annotation processes, and experience with quality assurance, often supported by a degree in a relevant field. Familiarity with annotation tools (like Labelbox or Supervisely), workflow management platforms, and sometimes agile or PMP certification is highly beneficial. Exceptional communication, attention to detail, and leadership abilities help you effectively coordinate teams and ensure project deliverables meet quality standards. These skills are essential for managing complex annotation projects efficiently, maintaining data integrity, and supporting successful machine learning outcomes.

How hard is it to get hired by data annotation?

Getting hired as a data annotation project manager typically requires relevant experience in project management, familiarity with annotation tools, and strong organizational skills. The role often involves coordinating teams and ensuring quality standards, with some positions requiring certifications or prior experience in data labeling environments. Competition varies depending on the company and location, but demonstrating technical knowledge and management ability can improve chances of hiring.

What is the salary of data annotation manager?

The salary of a Data Annotation Project Manager typically ranges from $60,000 to $100,000 annually, depending on experience, location, and company size. They often oversee teams using annotation tools and ensure quality standards are met in data labeling projects.

What are some common challenges faced by Data Annotation Project Managers, and how can they be managed effectively?

One of the primary challenges Data Annotation Project Managers face is ensuring high-quality, consistent labeling across large and sometimes distributed annotation teams. Managing tight deadlines while maintaining annotation accuracy requires effective training, clear guidelines, and regular quality checks. Additionally, balancing communication between data scientists, clients, and annotators is crucial to align expectations and resolve ambiguities quickly. Successful managers often implement robust feedback loops, leverage annotation tools with built-in quality control features, and foster an open environment for continuous improvement.

What is the difference between Data Annotation Project Manager vs Data Labeling Specialist?

AspectData Annotation Project ManagerData Labeling Specialist
CredentialsTypically requires project management experience, certifications in data management or related fieldsOften requires basic technical skills, familiarity with labeling tools, sometimes certifications in data annotation
Work EnvironmentOversees teams, manages projects, coordinates workflows in office or remote settingsPerforms labeling tasks, often in a remote or on-site environment, focused on data tagging
Employer & Industry UsageUsed by tech companies, AI firms, and data service providers for managing annotation projectsEmployed within similar industries, focusing on executing labeling tasks under supervision

The main difference is that the Data Annotation Project Manager oversees and coordinates annotation projects, ensuring quality and deadlines, while the Data Labeling Specialist focuses on executing the labeling tasks themselves. Both roles are essential in the data annotation process but differ in responsibilities and scope.

What is a Data Annotation Project Manager?

A Data Annotation Project Manager is responsible for overseeing projects that involve labeling and categorizing data, such as images, text, or audio, to train machine learning models. They coordinate teams of annotators, manage project timelines, and ensure the quality and accuracy of the annotated data. This role often acts as a bridge between data scientists, clients, and annotation teams, ensuring project requirements are met efficiently and effectively.
What are popular job titles related to Data Annotation Project Manager jobs in Federal Way, WA? For Data Annotation Project Manager jobs in Federal Way, WA, the most frequently searched job titles are:
What job categories do people searching Data Annotation Project Manager jobs in Federal Way, WA look for? The top searched job categories for Data Annotation Project Manager jobs in Federal Way, WA are:
What cities near Federal Way, WA are hiring for Data Annotation Project Manager jobs? Cities near Federal Way, WA with the most Data Annotation Project Manager job openings:
Infographic showing various Data Annotation Project Manager job openings in Federal Way, WA as of June 2026, with employment types broken down into 94% Full Time, and 6% Part Time. Highlights an 81% In-person, 6% Hybrid, and 13% Remote job distribution, with an average salary of $133,580 per year, or $64.2 per hour.
Data Annotation Specialist - Seattle (On Site)

Data Annotation Specialist - Seattle (On Site)

Welo Data

Seattle, WA

Full-time

Posted 11 days ago


Job description

OVERVIEW

Welo Data is looking for a skilled Data Analyst to join our team and contribute to advancing AI technologies. This role offers a unique opportunity to engage directly with cutting-edge AI products, supporting the refinement and performance of machine learning models through precise data analysis and quality assurance.

Project Details
Job Title: Data Analyst
Location: Seattle (On-site)
Hours: Full-time, 40 hours per week
Start Date: November 2025
Employment Type: W2 Full-Time Employee

Must have valid work authorization in the US (Welocalize does not sponsor VISAs at this time).

This role is an incredible chance to be at the forefront of AI technology, helping shape the future by testing new products, updating machine learning models, and ensuring high-quality data for impactful AI solutions.
Key Responsibilities
  • Test new AI products and provide actionable feedback to improve functionality and user experience.
  • Conduct detailed data annotation and quality assurance of natural language datasets following established guidelines.
  • Collaborate in updating and refining machine learning models to boost accuracy and effectiveness.
  • Analyze data for consistency, relevancy, and alignment with project goals.
  • Perform quality control to identify and report anomalies, error patterns, and discrepancies.
  • Use basic data analysis methods to extract insights and support continuous improvement.
  • Prepare clear and concise reports on findings, including observations on data quality, AI model performance, and user feedback.
Preferred Qualifications
  • University degree in linguistics, translation, or a related field.
  • 3-5 years of professional linguistics experience.
  • Strong analytical skills with the ability to detect patterns and anomalies.
  • Excellent communication skills and the ability to work collaboratively in a fast-paced environment.
  • Adaptability to evolving priorities and project requirements.
Benefits
  • Paid Sick Time & Paid Holiday (combined): 15 days
  • Paid Holidays: Memorial Day and Labor Day
  • Medical Insurance (subject to eligibility requirements)
  • Dental Insurance
  • Vision Insurance
  • Health Savings Account (HSA)
  • Voluntary Life Insurance
  • Accident, Critical Illness, and Hospital Indemnity Insurance
  • Telemedicine Benefit
  • 401(k) Retirement Plan
  • Employee Assistance Program
Please note that in order to verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment.

To know more details (Click here)

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.  In addition, we employ anti-fraud checks to ensure all candidates meet the requirements of the program.


As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.

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.