ZipRecruiter

Log In

1

Contract Data Annotation Jobs in Seattle, WA (NOW HIRING)

YO AI Labs

Chemistry Expert - Remote

Seattle, WA · Remote

$75 - $100/hr

Contract Location: Remote Scope of Work: * Produce authoritative, accurate, and well-explained ... Experience with AI, data annotation, or digital content development projects is advantageous but ...

New

YO AI Labs

Chemistry Expert - Remote

Seattle, WA · Remote

$75 - $100/hr

Contract Location: Remote Scope of Work: * Produce authoritative, accurate, and well-explained ... Experience with AI, data annotation, or digital content development projects is advantageous but ...

New

next page

Showing results 1-20

All JobsContract Data Annotation JobsContract Data Annotation Jobs in Seattle, WA

Contract Data Annotation information

What is a contract data annotation?

A contract data annotation job involves labeling or tagging data—such as images, text, audio, or video—according to specific guidelines, usually on a temporary or project-based contract. These annotations help train machine learning models by providing accurate, human-labeled examples for algorithms to learn from. Contract workers are typically hired for a set period or project and may work remotely or on-site, depending on the employer. The work requires attention to detail, adherence to quality standards, and sometimes familiarity with specialized annotation tools.

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

To thrive as a Contract Data Annotation Specialist, you need a keen eye for detail, strong analytical skills, and familiarity with data labeling standards, often supported by experience in data management or related fields. Proficiency with annotation platforms (such as Labelbox, Prodigy, or CVAT) and basic knowledge of data formats like JSON or XML are commonly required. Excellent communication, time management, and the ability to work independently help individuals excel in this often remote and deadline-driven role. These skills ensure high-quality, accurate data annotations that are vital for training reliable machine learning models.

What are some common challenges faced by contract data annotation professionals, and how can they be effectively managed?

Contract data annotation professionals often encounter challenges such as maintaining consistency in labeling, managing tight project deadlines, and ensuring data privacy. These challenges can be effectively managed by following detailed annotation guidelines, utilizing collaborative tools for team communication, and participating in regular quality assurance checks. Staying organized and proactive about seeking clarification from project leads also helps ensure high-quality, accurate results and a smooth workflow.

What is the difference between Contract Data Annotation vs Data Labeler?

AspectContract Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, project-basedRemote or on-site, task-based
Industry UsageAI/ML training, tech companiesAI/ML training, tech companies
Job FocusAnnotating data for machine learning modelsLabeling data to improve AI algorithms

Contract Data Annotation involves completing specific annotation projects for AI training, often on a contractual basis. Data Labelers focus on labeling data to enhance machine learning models, typically performing similar tasks. Both roles require attention to detail and are used in AI/ML industries, but Contract Data Annotation emphasizes project-based work with defined deliverables.

Is data annotation still hiring?

Data annotation roles are currently in demand as companies continue to develop AI and machine learning models. Many positions are available for remote work, often requiring basic computer skills and attention to detail, with some roles offering flexible schedules. Job availability can vary by industry and region, so checking specific job boards is recommended.

Is it hard to get hired for contract data annotation?

Contract data annotation jobs are generally accessible to individuals with basic computer skills and attention to detail. The hiring process often involves completing a skills test or sample annotation task, and some roles may require familiarity with specific tools or platforms. Competition can vary depending on the demand and the company's requirements, but many positions are available for entry-level candidates.

What are the most commonly searched types of Data Annotation jobs in Seattle, WA?

The most popular types of Data Annotation jobs in Seattle, WA are:

What are popular job titles related to Contract Data Annotation jobs in Seattle, WA?

For Contract Data Annotation jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Contract Data Annotation jobs in Seattle, WA look for?

The top searched job categories for Contract Data Annotation jobs in Seattle, WA are:

Contract Data Annotation jobs near you
Infographic showing various Contract Data Annotation job openings in Seattle, WA as of September 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 100% In-person job distribution.

Senior Technical Program Manager (AI/ML)

Seattle, WA • On-site

MDAEdge
Custom Software Development Services • 51 - 200 employees
Learn more about MDAEdgeexternal

Full-time

Re-posted 14 days ago

Job description

Job Summary:
MDAEdge is seeking a Technical Program Manager to lead data annotation programs for AI research. This role combines program management, data operations, and AI/ML to deliver scalable, high-quality data labeling aligned with research and product needs.
Responsibilities:
• Drive end-to-end data annotation programs, including scoping, delivery, and post-mortem analysis.
• Collaborate with AI research leaders, researchers, data scientists, ML engineers, and product managers to define data needs, metrics, and guidelines.
• Manage vendors and internal teams, handling contracts, SLAs, quality standards, and throughput.
• Design quality control pipelines, annotation tools, and feedback loops for scalable data quality.
• Partner with engineering to enhance annotation infrastructure, workflows, and data pipelines.
• Support data governance, including privacy, security, ethics, and compliance.
• Track metrics like cost, quality, speed, and volume; report progress to stakeholders.
• Coordinate internal adoption of AI products via onboarding, workflows, and change management.
• Standardize processes to measure, monitor, and improve data quality across teams and datasets.
• Engage customers and partners in workshops, pilots, and feedback for continuous improvement.
Qualifications:
Required:
• Bachelor's or Master's in Computer Science, Data Science, Machine Learning, Information Systems, or equivalent experience.
• 7+ years in technical program management, project management, or operations in data/AI/ML environments.
• Strong knowledge of ML workflows, data pipelines, and annotation lifecycles.
• Experience leading large-scale data labeling or collection with third-party vendors.
• Familiarity with big data platforms and data warehousing.
• Advanced SQL skills for analytics, tracking, forecasting, visualization, reports, and dashboards.
• Proven ability to perform root cause analysis on data and processes for business insights.
• Excellent organizational, problem-solving, communication, negotiation, and analytical skills.
• Experience documenting standard operating procedures.
• Ability to influence cross-functional teams and deliver complex projects on time with high quality.
• Self-motivated; thrives independently and in teams.
Preferred:
• Knowledge of GPU technology in generative AI/ML.
• Familiarity with Apache Spark, Delta Lake, MLflow.
Company:
The world doesn't have a talent shortage. It has a talent alignment problem. MDA Edge exists to fix that. Founded in , the company is headquartered in Sheridan, WY, US, , with a team of 51-200 employees. The company is currently Growth Stage.

Apply