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Data Annotation For Ai Jobs in Minnesota (NOW HIRING)

Thomson Reuters

Distinguished Engineer, AI Threat Defense

Eagan, MN · On-site

$60 - $80/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Model and data poisoning * AI supply-chain compromise * Model denial-of-service / denial-of-wallet attacks * Model, prompt, and intellectual-property theft Own technical monitoring and response for ...

THOMSON REUTERS

Distinguished Engineer, AI Threat Defense

Eagan, MN · On-site

$60 - $80/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Model and data poisoning * AI supply-chain compromise * Model denial-of-service / denial-of-wallet attacks * Model, prompt, and intellectual-property theft Own technical monitoring and response for ...

Programmers.io

AI Lead

Minneapolis, MN · On-site

... data storage solutions (e.g., Azure Blob Storage, Cosmos DB, etc.). o Experience with DevOps practices for machine learning, including CI/CD for AI systems, containerization (Docker), and ...

UnitedHealth Group

Lead AI Engineer - Remote

Eden Prairie, MN · On-site +1

$145K - $249K/yr

  • Retirement

Apply PII redaction pipelines on ingested documents and enforce data security using Model Context Protocol (MCP) * Deploy AI backends using FastAPI and Docker with OpenTelemetry for system-wide ...

UnitedHealth Group

Lead AI Engineer - Remote

Eden Prairie, MN · On-site +1

$145K - $249K/yr

  • Retirement

Apply PII redaction pipelines on ingested documents and enforce data security using Model Context Protocol (MCP) * Deploy AI backends using FastAPI and Docker with OpenTelemetry for system-wide ...

Vervint

Director of Data Intelligence

Minneapolis, MN · On-site +1

Reporting to the President & Chief Consulting Officer, this leader is accountable for positioning Data & AI as a core growth engine for the firm. You'll bring a mix of strategic vision, hands-on ...

Strategic Education

Data Scientist II

Minneapolis, MN · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The ideal candidate has strong analytical skills, a keen eye for data, and a passion for applying AI to real-world problems. Key Objectives: * Deliver measurable business impact using machine ...

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Data Annotation For Ai information

What is data annotation for AI?

Data annotation for AI is the process of labeling or tagging data—such as text, images, audio, or video—to make it understandable for machine learning models. Annotators add relevant information to raw data, helping AI systems learn to recognize patterns and make accurate predictions. This step is crucial for training, validating, and testing AI algorithms, especially in tasks like computer vision and natural language processing. High-quality data annotation directly impacts the effectiveness and reliability of AI applications.

What are some common challenges faced by data annotators working on AI projects, and how can they be addressed?

Data annotators for AI often encounter challenges such as maintaining consistency across large datasets, understanding ambiguous labeling instructions, and managing repetitive tasks. To address these issues, it's important to actively seek clarification on guidelines, participate in team discussions to align on labeling standards, and use annotation tools that flag inconsistencies. Regular feedback sessions with project leads also help improve accuracy and efficiency, fostering a collaborative and supportive work environment.

What are the key skills and qualifications needed to thrive as a data annotation specialist for AI, and why are they important?

To thrive as a Data Annotation Specialist for AI, you need a keen eye for detail, a solid understanding of data labeling concepts, and often a background in the relevant domain (such as language, images, or audio). Proficiency with annotation platforms, data management systems, and basic familiarity with tools like Excel or Python can be highly valuable. Strong communication, consistency, and time management skills help ensure accuracy and meet project deadlines. These abilities are crucial because high-quality, well-annotated data is foundational for training reliable and effective AI models.

What is the difference between Data Annotation For Ai vs Data Labeler?

AspectData Annotation For AiData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech companies, AI projectsRemote or on-site, data processing companies
Industry UsageArtificial Intelligence, Machine LearningData management, content moderation
Job FocusPreparing data for AI algorithms through annotationLabeling data for various purposes, including AI

Data Annotation For Ai involves preparing datasets specifically for training AI models, focusing on detailed annotations. Data Labeler is a broader role that includes labeling data for multiple purposes, including AI but also other data management tasks. While both roles require similar skills, Data Annotation For Ai is more specialized towards AI development projects.

What are popular job titles related to Data Annotation For Ai jobs in Minnesota?

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What job categories do people searching Data Annotation For Ai jobs in Minnesota look for?

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What cities in Minnesota are hiring for Data Annotation For Ai jobs?

Cities in Minnesota with the most Data Annotation For Ai job openings:

Data Annotation For Ai jobs near you
Infographic showing various Data Annotation For Ai job openings in Minnesota as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 3% Contract, and 1% Nights. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

AI Developer/ Architect

Delan Associates, Inc.

Saint Paul, MN • On-site

Contractor

Posted 6 days ago

Job description

The AI Developer 4 is a principal level expert who provides technical vision and organizational leadership for AI initiatives while remaining hands on in writing code.
This role defines and owns the enterprise wide AI technical architecture, leads highly complex and high impact AI transformations, and serves as a trusted subject matter expert to executive leadership.
The AI Developer 4 establishes governance and ethical AI frameworks, sets long term technical standards, mentors top technical talent, and cultivates future leaders.
In addition, this role anticipates industry trends and guides strategic investment in emerging AI technologies. Ideal candidates hold a bachelor's degree in computer science or a related field, have over 15 years of experience in software engineering and applied AI, demonstrate strong Python proficiency, possess proven experience designing scalable distributed AI systems, and are recognized experts in AI/ML with enterprise scale impact, supported by extensive experience in system architecture, cloud platforms, data ecosystems, and strong leadership and strategic communication skills.

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