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Full Time Machine Learning Data Annotation Jobs in Minneapolis, MN

US Bank

Senior Data Scientist

Minneapolis, MN · On-site

$132K - $155K/yr

... machine learning techniques and algorithms - Experience in python/R/SAS/SQL for data extraction, data mining, and predictive analytics - Demonstrated project management skills - Effective ...

General Mills

Senior Data Scientist

Minneapolis, MN · On-site +1

$110K - $184K/yr

Strong foundation in machine learning, statistical thinking, and/or analytical problem-solving ... Candidates must be currently authorized to work in the United States on a full-time basis SALARY ...

3M

AI/Machine Learning Engineer

Maplewood, MN

$143K/yr

Coursework or experience in algorithms, data structures, operating systems, concurrency, parallel ... Good Faith Posting Date Range 09/04/2026 To 10/04/2026 Or until filled All US-based 3M full time ...

New

3M

AI/Machine Learning Engineer

Maplewood, MN · On-site

$143K/yr

Coursework or experience in algorithms, data structures, operating systems, concurrency, parallel ... Good Faith Posting Date Range 09/04/2026 To 10/04/2026 Or until filled All US-based 3M full time ...

New

UnitedHealth Group

Sr Data Scientist - Remote

Minnetonka, MN · On-site +1

$91K - $163K/yr

The successful candidate will leverage statistical modeling, machine learning, predictive analytics ... The salary for this role will range from $91,700 - $163,700 annually based on full-time employment.

UnitedHealth Group

Sr Data Scientist - Remote

Minnetonka, MN · On-site +1

$91K - $163K/yr

The successful candidate will leverage statistical modeling, machine learning, predictive analytics ... The salary for this role will range from $91,700 - $163,700 annually based on full-time employment.

Micron

ASIC Gen-AI Data Scientist

Minneapolis, MN · On-site +1

$119K - $286K/yr

Machine Learning Production: Develop and productionize machine learning and deep learning models ... The US base salary range that Micron Technology estimates it could pay for this full-time position ...

Dlapiper

Data Scientist

Minneapolis, MN · On-site +1

A specialization in machine-learning, artificial intelligence, cognitive science or data science is preferred. Must be self-driven, curious and creative. * Experience must include creating and using ...

Accelint

Data Scientist

Saint Paul, MN · On-site

$105K - $126K/yr

Data Scientist * Full Time * Onsite/Hybrid Preferred The Data Scientist is responsible for ... The Data Scientist will apply knowledge of statistics, machine learning, programming, and data ...

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All JobsMachine Learning Data Annotation JobsFull Time Machine Learning Data Annotation JobsFull Time Machine Learning Data Annotation Jobs in Minneapolis, MN

Full Time Machine Learning Data Annotation information

See Minneapolis, MN salary details

$39.1K

$128.1K

$205.1K

How much do full time machine learning data annotation jobs pay per year?

As of Sep 6, 2026, the average yearly pay for full time machine learning data annotation in Minneapolis, MN is $128,114.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,800.00 and $142,000.00 per year, depending on experience, location, and employer.

What is a full time machine learning data annotation job?

Full time machine learning data annotation jobs involve labeling, tagging, or categorizing data such as images, text, audio, or video to help train machine learning models. Data annotators play a crucial role in ensuring that AI systems learn from high-quality, accurately labeled datasets. These positions often require attention to detail, consistency, and sometimes familiarity with the subject matter or specialized tools. Full-time roles may be remote or onsite and can span industries like autonomous vehicles, healthcare, retail, and more.

What are some common challenges faced by machine learning data annotators, and how are these typically addressed within a team?

Machine learning data annotators often encounter challenges such as maintaining consistency in labeling, handling ambiguous data, and meeting tight deadlines for large datasets. Teams usually address these by establishing clear annotation guidelines, conducting regular training sessions, and implementing quality assurance processes like peer reviews and spot checks. Collaboration with data scientists and project managers is also common, ensuring that annotators can ask questions and clarify uncertainties, leading to higher-quality labeled data and a supportive work environment.

What are the key skills and qualifications needed to thrive as a full time machine learning data annotation specialist, and why are they important?

To thrive as a Full Time Machine Learning Data Annotation Specialist, you need strong attention to detail, basic data literacy, and familiarity with data labeling concepts, often supported by a high school diploma or equivalent. Proficiency in specialized annotation platforms, spreadsheet tools, and sometimes knowledge of Python or labeling frameworks is typically required. Reliability, patience, and effective communication are valuable soft skills for ensuring accuracy and collaborating with team members. These skills and qualities are crucial because they directly impact the quality of training data, which is essential for developing effective machine learning models.

What is the difference between Full Time Machine Learning Data Annotation vs Data Labeling Specialist?

AspectFull Time Machine Learning Data AnnotationData Labeling Specialist
CredentialsHigh school diploma or equivalent; some roles prefer technical certificationsHigh school diploma or equivalent; training often provided on the job
Work EnvironmentOffice or remote; collaborative with data science teamsRemote or office; focused on labeling tasks
Industry UsageUsed across AI/ML companies, tech firms, and startupsCommon in AI/ML, data services, and outsourcing companies
Job FocusCreating labeled datasets for machine learning modelsAnnotating data such as images, videos, or text for AI training

Full Time Machine Learning Data Annotation involves creating high-quality labeled datasets for AI models, often requiring technical understanding. Data Labeling Specialists focus on annotating data accurately, typically with less emphasis on technical skills. Both roles are essential in AI development but differ mainly in scope and technical complexity.

What are the most commonly searched types of Machine Learning Data Annotation jobs in Minneapolis, MN?

The most popular types of Machine Learning Data Annotation jobs in Minneapolis, MN are:

What are popular job titles related to Full Time Machine Learning Data Annotation jobs in Minneapolis, MN?

For Full Time Machine Learning Data Annotation jobs in Minneapolis, MN, the most frequently searched job titles are:

What job categories do people searching Full Time Machine Learning Data Annotation jobs in Minneapolis, MN look for?

The top searched job categories for Full Time Machine Learning Data Annotation jobs in Minneapolis, MN are:

Full Time Machine Learning Data Annotation jobs near you

Principal Data Scientist - Remote

UnitedHealth Group

Eden Prairie, MN • On-site, Remote

$112K - $193K/yr

Full-time

Retirement

Re-posted yesterday

Key responsibilities

  • Lead high-impact AI initiatives by designing and building scalable, secure, and efficient AI architectures and models.

  • Perform analysis, modeling, and deployment of healthcare data and machine learning models, including optimizing and validating them for production.

  • Establish automated processes for large-scale data analysis, machine learning development, and research emerging AI trends to incorporate into solutions.

UnitedHealth Group rating

7.6

Company rating: 7.6 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

192nd of 898 rated healthcare providers

Job description

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together.
The Clinical Decision Support (CDS) Engineering team, a unit within the Optum Insight Technology organization, is responsible for building commercial products that help payers and providers with administrative- and clinician-focused CDS solutions. In this role as a Principal Data Scientist, you will lead high-impact AI initiatives characterized by scale and complexity. You will architect robust, secure AI systems, train state-of-the-art transformer and multimodal models, and bridge the gap between AI research and production software engineering. By extracting deep insights from healthcare data and maintaining the highest standards of responsible and ethical AI, you will help shape the next generation of intelligent health solutions.
You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.
Primary Responsibilities:
  • Drive end-to-end generative AI and machine learning projects that have a high degree of ambiguity, scale, and complexity
  • Design robust AI architectures, ensuring that systems are scalable, secure, and efficient; select appropriate technologies, frameworks, and methodologies
  • Build machine learning models, perform proof-of-concept experiments, optimize and deploy models to production, and partner with software engineers to productionize ML models
  • Perform hands-on analysis and modeling of healthcare data sets to develop insights that increase business value
  • Run A/B experiments, gather data, and perform statistical analysis; continuously assess AI system performance and optimize algorithms and models to improve accuracy and efficiency
  • Establish scalable, efficient, automated processes for large-scale data analysis, machine learning model development and validation, and MLOps
  • Research and implement innovative machine learning approaches, evaluate emerging trends to inform solution design, and translate cutting-edge AI advancements into production-ready capabilities that can be re-used across the enterprise
  • Uphold ethical AI principles by embedding fairness, transparency, and accountability throughout the model development lifecycle
  • Mentor and help recruit AI/ML scientists and machine learning engineers to the team

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.
Required Qualifications:
  • 10+ years of industry or academic experience in machine learning or a related data science field
  • 5+ years of experience building machine learning models for business applications
  • 5+ years of experience leading technical teams or complex AI/ML projects
  • 4+ years of equivalent technical experience in software development/data science
  • 3+ years of experience with Python programming and deep learning frameworks (e.g., PyTorch or TensorFlow)
  • 3+ years of experience with state-of-the-art ML architectures (e.g., Transformers/LLMs, multimodal modeling) and transformer fine-tuning

Preferred Qualifications:
  • Experience working with complex healthcare datasets and clinical/claims analytics
  • Practical experience with public cloud AI technology stacks, deployment, and MLOps methodologies (AWS preferred)
  • Experience with big data processing tools such as Hadoop and Spark
  • Experience with state-of-the-art ML algorithms and architectures (e.g., Transformers/LLMs, state space models such as Mamba, GNNs), legacy architecture maintenance/migration, and tradeoffs between pretraining from scratch vs. adapting foundation models

*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy.
Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $112,700 - $193,200 annually based on full-time employment. We comply with all minimum wage laws as applicable.
Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.
UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.
UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment.

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