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Ai Labelling information

What is an AI labelling?

An AI labelling job involves annotating data—such as images, text, audio, or video—to help train machine learning models. This process includes tasks like tagging objects in images, transcribing speech, or categorizing text. The labelled data is crucial for AI systems to learn and make accurate predictions. These jobs are commonly found in industries like tech, healthcare, and autonomous driving. Attention to detail and consistency are key skills for this role.

What are the key skills and qualifications needed to thrive in AI labelling?

To thrive in an AI Labelling role, you need attention to detail, basic data analysis skills, and the ability to follow complex guidelines, with many roles requiring at least a high school diploma or equivalent. Familiarity with data annotation tools, image or text labeling platforms, and sometimes basic scripting or database systems is beneficial. Strong communication, time management, and the ability to work both independently and as part of a team are valuable soft skills. These competencies ensure the consistent and accurate labeling of data, which is critical for training high-quality AI and machine learning models.

What are some typical challenges faced in AI labelling roles and how can they be managed?

One common challenge in AI Labelling roles is maintaining accuracy and consistency when labeling large volumes of data according to detailed guidelines, which can become repetitive or mentally taxing. Managing these challenges often involves taking regular breaks, double-checking work, and staying up-to-date with any updates to annotation standards provided by the team. Collaborating with supervisors and peers to clarify uncertainties and seek feedback also helps ensure high-quality output. Over time, professionals in this role often develop efficient workflows and a keen eye for detail, opening doors to advancement into quality assurance or project coordination positions within the data annotation field.

What are popular job titles related to Ai Labelling jobs in Vermont?

For Ai Labelling jobs in Vermont, the most frequently searched job titles are:

What job categories do people searching Ai Labelling jobs in Vermont look for?

The top searched job categories for Ai Labelling jobs in Vermont are:

Ai Labelling jobs near you
Infographic showing various Ai Labelling job openings in Vermont as of August 2026, with employment types broken down into 79% Full Time, 19% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Senior Microsoft Purview Data Security Engineer

Tunbridge, VT

2T Consulting
IT Services • 51 - 200 employees
Learn more about 2T Consultingexternal

$115K - $157K/yr

Full-time

Posted 9 days ago

Job description

Roles and Responsibilities
  • Design, implement, administer, and optimize enterprise Microsoft Purview architecture, governance models, policies, and operational processes.
  • Serve as a technical SME for Purview DLP, Information Protection, Sensitivity Labels, Insider Risk Management, Records Management, DSPM, eDiscovery, Audit, and Compliance Manager.
  • Configure and manage Sensitive Information Types (SITs), Exact Data Match (EDM), Trainable Classifiers, and data protection controls.
  • Develop and enforce data protection policies across Exchange, SharePoint, Teams, endpoints, and other Microsoft 365 workloads.
  • Design and implement data security and governance controls for Microsoft 365 Copilot and AI-enabled workloads.
  • Extend data protection and governance capabilities across Azure and multi-cloud environments.
  • Partner with Security Operations, Legal, Privacy, Compliance, and Cloud Engineering teams to translate regulatory requirements into technical controls.
  • Integrate Microsoft Purview with Microsoft Defender XDR and Microsoft Sentinel to improve security monitoring and incident response.
  • Develop PowerShell automation for Purview administration, policy management, reporting, and operational tasks.
  • Create security posture reports and dashboards using Power BI.
  • Conduct platform health checks, troubleshoot security and compliance issues, and continuously improve the data security posture.
  • Establish deployment, change management, documentation, and operational governance standards for data security solutions.
Required Qualifications
  • Bachelor’s degree in Cybersecurity, Computer Science, Information Technology, or equivalent practical experience.
  • 5+ years of information security engineering experience.
  • 3+ years of hands-on Microsoft Purview implementation and administration experience.
  • Strong experience implementing:
    • Microsoft Purview DLP
    • Information Protection and Sensitivity Labels
    • Sensitive Information Types (SITs)
    • Exact Data Match (EDM)
    • Trainable Classifiers
    • Insider Risk Management
    • Records Management
    • eDiscovery, Audit, and Compliance Manager
  • Hands-on experience with Microsoft Defender for Endpoint, Microsoft Intune, and Microsoft 365 security.
  • Strong PowerShell scripting and automation experience.
  • Experience integrating Microsoft security and compliance technologies with Microsoft Sentinel and Defender XDR.
  • Strong understanding of data protection, information governance, compliance, and security operations.
  • Knowledge of security and compliance frameworks such as NIST, ISO 27001, and GDPR.
  • Strong analytical, troubleshooting, communication, and stakeholder management skills.
Preferred Qualifications
  • Experience with Microsoft Purview Data Map, Data Security Posture Management (DSPM), and enterprise data discovery/scanning.
  • Experience securing and governing Microsoft 365 Copilot and AI-enabled technologies.
  • Experience developing Power BI security and compliance dashboards.
  • Strong knowledge of Zero Trust security principles.
  • Familiarity with HIPAA, PCI-DSS, SOX, and CCPA requirements.
  • Experience working in highly regulated or compliance-driven enterprise environments.

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