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Ai Tagging Jobs (NOW HIRING)

AI Lead/Architect

Chicago, IL · On-site

$57 - $78/hr

... tagging to improve contextual accuracy and response quality. • Build intuitive AI-driven applications using Databricks Apps (Streamlit/Dash) or modern web frameworks to enable business consumption ...

Job Title- Product Manager - AI Project Location - Hybrid at Oakland, CA office 2-3 days onsite in ... Strong understanding of model training pipelines, tagging systems, and metadata management.

Work closely with our AI and Data Engineering teams to build and maintain cutting-edge AI-tagging systems * Design, maintain, and run QA processes to validate data across hundreds of thousands of ...

Work closely with our AI and Data Engineering teams to build and maintain cutting-edge AI-tagging systems * Design, maintain, and run QA processes to validate data across hundreds of thousands of ...

Work closely with our AI and Data Engineering teams to build and maintain cutting-edge AI-tagging systems * Design, maintain, and run QA processes to validate data across hundreds of thousands of ...

Work closely with our AI and Data Engineering teams to build and maintain cutting-edge AI-tagging systems * Design, maintain, and run QA processes to validate data across hundreds of thousands of ...

Partner with Engineering infra and product teams to define tagging taxonomy, identify tagging gaps, and improve tagging to enable reporting. Make Cloud and AI spend billing data available in ...

Maintain lineage, catalog tagging, governance assumptions, and input/output documentation to support auditability and solution reliability. Evaluate AI tools and frameworks, including Mosaic AI, AI ...

Maintain lineage, catalog tagging, governance assumptions, and input/output documentation to support auditability and solution reliability. Evaluate AI tools and frameworks, including Mosaic AI, AI ...

Maintain lineage, catalog tagging, governance assumptions, and input/output documentation to support auditability and solution reliability. Evaluate AI tools and frameworks, including Mosaic AI, AI ...

Maintain lineage, catalog tagging, governance assumptions, and input/output documentation to support auditability and solution reliability. Evaluate AI tools and frameworks, including Mosaic AI, AI ...

Maintain lineage, catalog tagging, governance assumptions, and input/output documentation to support auditability and solution reliability. Evaluate AI tools and frameworks, including Mosaic AI, AI ...

Eliminate manual bottlenecks across reporting, tagging, and testing workflows. * Build AI agents supporting requirements review, architecture, coding, testing, debugging, and deployment. * Capture ...

Strong Git/GitHub skills, including branching strategies, pull requests, code reviews, tagging, releases, merges, and conflict resolution. * Experience using AI tools (e.g., ChatGPT, GitHub Copilot ...

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Ai Tagging information

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$39K

$114.3K

$150K

How much do ai tagging jobs pay per year?

As of Jul 23, 2026, the average yearly pay for ai tagging in the United States is $114,320.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,500.00 and $134,500.00 per year, depending on experience, location, and employer.

What does a typical day look like for someone in an AI Tagging role?

A typical day for an AI Tagging professional includes reviewing and labeling large sets of data—such as images, audio, or text—according to specific guidelines provided by the project. You may spend time collaborating with data scientists or project managers to clarify labeling instructions or resolve ambiguous cases. Work is usually structured with clear quality and productivity targets, and you might also participate in feedback sessions to improve annotation consistency. The pace can be steady, with periods of high concentration, and you may use specialized software platforms to manage your workflow. Team communication and attention to detail are key aspects of the job each day.

What are the key skills and qualifications needed to thrive in the Ai Tagging position, and why are they important?

To thrive in AI Tagging, you need strong attention to detail, data annotation skills, and familiarity with data quality standards, often backed by experience or coursework in information science or computer science. Familiarity with data labeling platforms, image and text annotation tools, and occasionally basic programming or scripting knowledge is beneficial. Strong organizational skills, patience, and the ability to work efficiently both independently and within a team distinguish top performers in this role. These skills ensure the accurate and efficient creation of high-quality labeled datasets that are essential for training and improving AI models.

What is an AI Tagging job?

An AI Tagging job involves labeling or annotating data to help train machine learning models. This can include tagging images, videos, text, or audio with relevant metadata so that AI systems can recognize patterns and improve accuracy. AI taggers follow specific guidelines to ensure consistency and quality in the annotations. It's a crucial step in developing AI systems for tasks like image recognition, natural language processing, and recommendation algorithms.

More about Ai Tagging jobs
What cities are hiring for Ai Tagging jobs? Cities with the most Ai Tagging job openings:
What are the most commonly searched types of Ai Tagging jobs? The most popular types of Ai Tagging jobs are:
What states have the most Ai Tagging jobs? States with the most job openings for Ai Tagging jobs include:
Infographic showing various Ai Tagging job openings in the United States as of July 2026, with employment types broken down into 73% Full Time, 24% Part Time, and 3% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution, with an average salary of $114,320 per year, or $55 per hour.

Solution Analyst - Digital Asset Management

Milwaukee Electric Tool Corporation

Milwaukee, WI • On-site

Other

Medical, Dental, Vision, Retirement

This job post has expired today. Applications are no longer accepted.


Job description

The DAM Administrator plays a critical role in managing and scaling Milwaukee Tool's Digital Asset Management ecosystem to support Product Experience Management (PXM), marketing operations, sales enablement, ecommerce, and global content distribution.

This role is responsible for maintaining the health, governance, organization, and optimization of the DAM platform, ensuring digital assets are structured, discoverable, accurate, compliant, and connected across enterprise systems and downstream channels.

Operating at the intersection of content, metadata, workflow, and technology, this individual partners cross-functionally with PXM, Brand, Creative, Digital, Ecommerce, IT, and external partners to improve asset accessibility, streamline workflows, enforce governance standards, and support scalable omnichannel content operations.

The role combines platform administration, metadata governance, taxonomy management, user enablement, automation support, and asset lifecycle management to ensure Milwaukee Tool's DAM evolves as a scalable enterprise capability rather than simply a file repository.

You'll be DISRUPTIVE through these duties and responsibilities:

  • Translate business needs into scalable DAM solutions: Partner with PIM, Brand, Creative, Digital, eCommerce, IT, and external partners to convert business requirements into scalable DAM structures, metadata models, workflows, taxonomy strategies, and asset governance standards.
  • Drive DAM governance and operational excellence: Establish and maintain DAM governance standards including metadata requirements, naming conventions, taxonomy structures, permissions, lifecycle policies, archival standards, and asset usage protocols to improve consistency, scalability, and usability across the organization.
  • Support platform strategy and ownership: Serve as a subject matter expert for the Digital Asset Management platform, contributing to roadmap prioritization, platform enhancements, workflow optimization, governance maturity, and long-term DAM scalability initiatives.
  • Optimize metadata and search experiences: Develop and maintain metadata schemas, controlled vocabularies, categories, collections, tags, and search configurations that improve discoverability, asset reuse, syndication readiness, and downstream channel distribution.
  • Manage asset lifecycle and content integrity: Oversee processes for asset ingestion, version control, approvals, expiration, archival, duplicate management, and deletion to ensure users have access to accurate, compliant, and current digital assets.
  • Enable scalable content distribution and syndication: Support the organization and delivery of product, marketing, sales, training, and brand assets across websites, eCommerce channels, portals, distributors, agencies, and downstream integrated platforms.
  • Leverage data and DAM insights to improve performance: Analyze DAM usage patterns, search behavior, metadata quality, duplicate content, asset engagement, and platform analytics to identify optimization opportunities and improve operational efficiency.
  • Enable cross-functional execution and adoption: Collaborate closely with PXM, Creative, Marketing, Digital, IT, and external partners to improve workflows, streamline asset operations, and support enterprise content scalability.
  • Support integrations and automation initiatives: Partner with Digital and IT teams to support integrations between DAM, PIM/PXM, CMS, eCommerce, and marketing platforms, while helping advance metadata automation, AI tagging, upload profiles, and workflow automation opportunities.
  • Advance DAM innovation and enterprise scalability: Stay informed on emerging DAM, PXM, AI tagging, metadata automation, and content operations trends to help improve discoverability, operational efficiency, governance maturity, and enterprise scalability.

The TOOLS you'll bring with you:

  • Bachelor's degree in Digital Marketing, Information Management, Library Science, Communications, Business, Information Systems, or a related field - or equivalent practical experience
  • 2 years+ of experience working with Digital Asset Management (DAM), Product Information Management (PIM), Product Experience Management (PXM), content operations, marketing technology, or enterprise digital platforms within a business, product, marketing, or eCommerce environment
  • Experience managing Digital Asset Management platforms such as Acquia DAM, Aprimo, Bynder, Adobe Experience Manager Assets, or similar technologies
  • Understanding of metadata governance, taxonomy structures, controlled vocabularies, asset organization, search optimization, and digital content lifecycle management best practices
  • Ability to translate business objectives into scalable DAM governance standards, metadata structures, workflows, operational processes, and platform solutions
  • Experience supporting integrations between DAM, PIM/PXM, CMS, eCommerce, marketing, or downstream content distribution platforms
  • Strong analytical and problem-solving skills, with the ability to identify operational inefficiencies, metadata quality gaps, duplicate assets, and optimization opportunities using platform data and insights
  • Strong communication and organizational skills, including the ability to simplify complex DAM concepts, manage competing priorities, document governance standards, and collaborate cross-functionally with technical and non-technical stakeholders

We provide these great perks and benefits:

  • Robust health, dental and vision insurance plans

  • Generous 401 (K) savings plan

  • Education assistance

  • On-site wellness, fitness center, food, and coffee service

  • And many more, check out our benefits siteHERE

Milwaukee Tool is an equal opportunity employer.
Apply Now