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Temporary Medical Data Annotation Jobs (NOW HIRING)

Gehc

Data Manager - AI Development

Waukesha, WI

Knowledge of medical imaging data formats and annotation tools (e.g., V7). * Exposure to regulated development environments (medical devices, healthcare software, or similar). * Understanding of data ...

Amazon

Catalog Specialist, RCX

Bellevue, WA · On-site

... Perform data annotation required to train and evaluate ML models effectively • Support data ... Starting Day 1 of employment, Amazon offers EAP, Mental Health Support, Medical Advice Line, 401(k) ...

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Temporary Medical Data Annotation information

What is the difference between Temporary Medical Data Annotation vs Medical Data Labeler?

AspectTemporary Medical Data AnnotationMedical Data Labeler
CredentialsBasic understanding of medical terminology, training in annotation toolsSimilar, often requires familiarity with medical terminology
Work EnvironmentRemote or on-site, healthcare or tech companiesRemote or on-site, healthcare or AI companies
Industry UsageUsed in AI training for medical imaging, EHR dataUsed in AI model development, data preparation
Search/Comparison IntentUnderstanding role differences, job requirementsClarifying job scope, responsibilities

Temporary Medical Data Annotation involves annotating medical data for AI training, often requiring specific medical terminology knowledge. Medical Data Labeler performs similar tasks, focusing on labeling data for machine learning. Both roles are essential in healthcare AI development, with overlapping skills and environments. The main difference lies in job titles used by employers and specific project scopes.

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Temporary Medical Data Annotation jobs near you
Infographic showing various Temporary Medical Data Annotation job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 84% Full Time, 6% Part Time, 1% Temporary, and 8% Contract. Highlights an 46% Physical, 1% Hybrid, and 53% Remote job distribution.
Data Manager - AI Development

Data Manager - AI Development

GE HealthCare

Waukesha, WI • On-site

Full-time

Posted 23 days ago

GE HealthCare rating

8.5

Company rating: 8.5 out of 10

Based on 130 frontline employees who took The Breakroom Quiz

61st of 416 rated machine equipment manufacturers

Job description

Job Description Summary
The Data Manager - AI Development is a key role within the AI Development team responsible for planning, coordinating, tracking, and governing data used to develop AI enabled medical device features. This role works closely with AI/ML engineers to define data needs for AI features, coordinates with internal and external data collection teams/clinical team, oversees annotation activities, and ensures data readiness, traceability, and compliance throughout the AI development lifecycle.
The role is execution focused and coordination driven, ensuring that the right data is available, prepared, and documented at the right time to support AI feature development, evaluation, and regulatory readiness. Strong planning, communication, and organizational skills are essential for success in this role.
Please note - this is a full time, onsite role located in Waukesha, WI.
Job Description
Roles and Responsibilities
Key Roles and Responsibilities
1. AI Data Planning & Requirements
  • Partner with AI/ML engineers and technical leads to define data requirements for AI features, including dataset scope, diversity, and usage intent.
  • Translate feature and model needs into clear data requirements that guide collection, annotation, and preparation activities.
  • Support creation and maintenance of AI data planning artifacts aligned with internal Quality Management System (QMS) requirements.

2. Data Collection Coordination
  • Coordinate with centralized and distributed data collection teams to support AI development needs.
  • Track data sourcing activities across multiple programs and stakeholders.
  • Maintain data collection dashboards that provide visibility into status, coverage, risks, and gaps.
  • Track data collection and annotation budget.

3. Annotation & Labeling Oversight
  • Coordinate data annotation activities with internal teams and external vendors.
  • Track annotation progress, throughput, and quality metrics.
  • Maintain annotation dashboards to ensure timely delivery aligned with AI development milestones.

4. Data Governance & Compliance Support
  • Support execution of AI data management practices including:
    • Data control planning
    • Data segregation between training, holdout, and testing datasets
    • Data preparation and inclusion criteria
    • Data traceability and usage documentation
  • Ensure datasets are properly documented and traceable to their original sources to support audits and regulatory submissions.
  • Act as a point of coordination to ensure data activities align with applicable QMS work instructions for AI development.

5. Program Tracking & Communication
  • Serve as the central coordination point for AI data activities across engineering, data operations, and program teams.
  • Proactively communicate status, risks, and dependencies to stakeholders.
  • Support planning reviews, design reviews, and readiness discussions with accurate data status reporting.

Required Qualifications
  • Bachelor's degree in Engineering, Computer Science, Data Science, Biomedical Engineering, or a related technical discipline with 4 years of experience.
  • Experience in data management, data operations, or program coordination roles supporting technical or engineering teams.
  • Demonstrated ability to plan, track, and coordinate complex workflows across multiple stakeholders.
  • Strong written and verbal communication skills, with the ability to translate technical needs into actionable plans.
  • Experience creating and maintaining dashboards (eg. PowerBI, excel, smartsheet) trackers, or reports for operational visibility.
  • Familiarity with structured data workflows(eg. SQL), including data collection, annotation, and dataset organization(eg. Python).
  • Ability to work effectively in cross-functional teams within a regulated or quality-driven environment.

Desired Characteristics
  • Experience supporting AI / machine learning development teams, particularly in healthcare or medical devices.
  • Familiarity with AI data lifecycle concepts, including training, validation, and testing datasets.
  • Knowledge of medical imaging data formats and annotation tools (e.g., V7).
  • Exposure to regulated development environments (medical devices, healthcare software, or similar).
  • Understanding of data governance concepts such as data traceability, segregation, and controlled usage.
  • Experience coordinating external vendors or annotation partners.
  • Comfort working with ambiguity and evolving requirements in early-stage AI feature development.
  • Experience with Microsoft Forms

Why Join Us?
  • Be at the forefront of AI-driven healthcare innovation.
  • Collaborate with a multidisciplinary team passionate about improving patient outcomes.
  • Shape the future of regulatory processes for cutting-edge medical technologies.

We will not sponsor individuals for employment visas, now or in the future, for this job opening.
Additional Information
GE HealthCare offers a great work environment, professional development, challenging careers, and competitive compensation. GE HealthCare is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
GE HealthCare will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).
While GE HealthCare does not currently require U.S. employees to be vaccinated against COVID-19, some GE HealthCare customers have vaccination mandates that may apply to certain GE HealthCare employees.
Relocation Assistance Provided: No

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