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Manager Ai Annotation Jobs in Wisconsin (NOW HIRING)

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Manager Ai Annotation information

What is the difference between Manager Ai Annotation vs Data Annotator?

AspectManager Ai AnnotationData Annotator
Required CredentialsBachelor's degree in related field, experience in AI projectsHigh school diploma or equivalent, on-the-job training
Work EnvironmentTeam management, project oversight, collaboration with data scientistsData labeling tasks, working with annotation tools
Industry UsageAI development, machine learning projectsData preparation for AI models
Search & Comparison IntentUnderstanding managerial roles in AI annotationEntry-level annotation tasks

The main difference between Manager Ai Annotation and Data Annotator lies in their responsibilities and experience. Managers oversee annotation projects, coordinate teams, and ensure quality, requiring leadership skills and experience. Data Annotators focus on labeling data accurately under supervision. Managers typically have higher credentials and work in strategic roles, while annotators perform the hands-on labeling tasks essential for AI training.

What are the most commonly searched types of Ai Annotation jobs in Wisconsin? The most popular types of Ai Annotation jobs in Wisconsin are:
What are popular job titles related to Manager Ai Annotation jobs in Wisconsin? For Manager Ai Annotation jobs in Wisconsin, the most frequently searched job titles are:
What cities in Wisconsin are hiring for Manager Ai Annotation jobs? Cities in Wisconsin with the most Manager Ai Annotation job openings:
Data Manager - AI Development

Data Manager - AI Development

GE HealthCare

Waukesha, WI • On-site

Full-time

Posted 2 days ago


GE HealthCare rating

8.3

Company rating: 8.3 out of 10

Based on 135 frontline employees who took The Breakroom Quiz

92nd of 430 rated machine equipment manufacturers


Job description

Job Summary:
GE HealthCare is a leader in healthcare innovation, and they are seeking a Data Manager for their AI Development team. This role is responsible for planning, coordinating, tracking, and governing data used to develop AI-enabled medical device features, working closely with AI/ML engineers and various stakeholders to ensure data readiness and compliance throughout the development lifecycle.
Responsibilities:
• 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.
• 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.
• 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.
• 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.
• 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.
Qualifications:
Required:
• 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.
Preferred:
• 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
Company:
Every day millions of people feel the impact of our intelligent devices, advanced analytics and artificial intelligence. Founded in 1989, the company is headquartered in Bethlehem, USA, with a team of 10001+ employees. The company is currently Late Stage.

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