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Data Annotation Project Manager Jobs in Federal Way, WA

Collaborate remotely with project teams to improve AI models and workflows. Required Skills ... Data Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving

New

Collaborate remotely with project teams to improve AI models and workflows. Required Skills ... Data Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving

New

AI Data Science Expert - Remote

Seattle, WA ยท Remote

$100 - $200/hr

Collaborate remotely with project teams to improve AI models and workflows. Required Skills ... Data Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving

New

AI Data Science Expert - Remote

Seattle, WA ยท Remote

$100 - $200/hr

Collaborate remotely with project teams to improve AI models and workflows. Required Skills ... Data Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving

New

AI Finance Expert - Remote

Seattle, WA ยท Remote

$100 - $200/hr

... project at the intersection of finance and artificial intelligence . In this role, you will help ... Data Annotation * Problem-Solving * Independent Research * Attention to Detail Preferred ...

New

AI Finance Expert - Remote

Seattle, WA ยท Remote

$100 - $200/hr

... project at the intersection of finance and artificial intelligence . In this role, you will help ... Data Annotation * Problem-Solving * Independent Research * Attention to Detail Preferred ...

New

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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 Aug 14, 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 are met, often requiring familiarity with annotation tools and project management skills.

What are the key skills and qualifications needed to thrive as a data annotation project manager?

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.

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 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.

AI Data Scientist Expert - Remote

YO AI Labs

Seattle, WA โ€ข Remote

$100 - $200/hr

Part-time

Posted 3 days ago

New


Job description

Job Title: AI Data Science Domain Expert

Job Type: Contractor (Part-Time)
Location: Remote

Job Overview

We are seeking experienced AI Data Science Domain Experts to contribute their expertise to an innovative project focused on advancing next-generation AI systems. In this role, you will review, evaluate, and refine AI-generated technical and analytical content to improve model accuracy, reasoning, and overall performance. No prior AI experience is required—your data science expertise, analytical thinking, and communication skills are what matter most.

Key Responsibilities
  • Review, edit, and refine AI-generated content for accuracy, clarity, and technical relevance.
  • Develop, optimize, and evaluate prompts to improve AI model performance.
  • Conduct rubric-based assessments of AI outputs and provide structured feedback.
  • Perform independent research and fact-checking to validate technical information.
  • Annotate data and support quality assurance initiatives for AI training.
  • Interpret complex datasets and prepare clear technical reports and summaries.
  • Collaborate remotely with project teams to improve AI models and workflows.
Required Skills
  • Critical Thinking
  • Analytical Reasoning
  • Prompt Engineering
  • AI Output Evaluation
  • Quality Assurance
  • Technical Documentation
  • Technical & Report Writing
  • Content Review & Editing
  • Data Annotation
  • Data Interpretation
  • Fact Checking
  • Independent Research
  • Problem-Solving
  • Attention to Detail
Preferred Qualifications
  • 3+ years of experience in Data Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.
  • Experience producing or reviewing research papers, analytical reports, technical documentation, experiment summaries, or data-driven recommendations.
  • Strong analytical reasoning, critical thinking, and written communication skills.
  • Experience with data annotation, content review, or rubric-based evaluation is preferred.
  • Familiarity with prompt engineering, AI output evaluation, fact-checking, or RLHF is a plus.
  • Master's, MBA, PhD, or other advanced degree is preferred.