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Full Time Machine Learning Data Annotation Jobs in Minneapolis, MN

DailyPay

Senior Machine Learning Engineer

Minneapolis, MN · Remote

$170K - $190K/yr

We are seeking a Senior Machine Learning Engineer to join our AI & ML team in New York City. You ... You will work closely with data scientists, engineers, and product stakeholders to deliver high ...

Bespoke Labs

Machine Learning Engineer

Plymouth, MN

Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment orchestration * Run and scale training experiments on cloud or HPC ...

Bespoke Labs

Machine Learning Engineer

Minneapolis, MN · On-site

Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment orchestration * Run and scale training experiments on cloud or HPC ...

Bespoke Labs

Machine Learning Engineer

Plymouth, MN · On-site

Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment orchestration * Run and scale training experiments on cloud or HPC ...

Precision Technologies Corp

GCP ML Architect - Data

Chaska, MN · On-site

$68.25 - $88/hr

Chaska MN Hire type: Full-TIme Detailed JD : * Responsible for designing, implementing, and managing data and machine learning solutions on Google Cloud Platform * Key Responsibilities: * Design end ...

US Bank

Data Scientist

Minneapolis, MN · On-site

What You'll DoDevelop Machine Learning & Predictive Analytics Solutions * Design, develop ... Transform Data into Actionable Insights * Gather, integrate, and analyze large volumes of ...

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Showing results 21-40

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 9, 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

Emerging Technology Solutions Architect - Machine Learning

Hopkins, MN

US Bank
Banking and Credit Intermediation • 10K+ employees
Learn more about US Bankexternal

$64 - $84.25/hr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 15 days ago

U.S. Bank rating

8.1

Company rating: 8.1 out of 10

Based on 364 frontline employees who took The Breakroom Quiz

67th of 176 rated banks

Job description

At U.S. Bank, we're on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed. We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career. Try new things, learn new skills and discover what you excel at-all from Day One.

Job Description

U.S. Bank is seeking an Emerging Technology Solutions Architect - Machine Learning to evaluate, design, and guide adoption of machine learning technologies across the enterprise. This role focuses on identifying emerging ML capabilities, assessing enterprise fit, and defining scalable solutions that enable advanced analytics, predictive modeling, and AI-driven business outcomes while aligning to enterprise standards.

The Emerging Technology Solutions Architect will partner across data engineering, platform engineering, data science, and risk/security teams to evaluate technologies, define architecture patterns, and enable implementation through strong technical leadership and hands-on solution design. This role will help shape the future of machine learning capabilities at U.S. Bank by establishing scalable, secure, and reusable solutions that accelerate responsible innovation.

Responsibilities
  • Evaluate emerging machine learning technologies, platforms, frameworks, and tooling ecosystems for enterprise adoption.
  • Assess ML technologies and services including Azure Machine Learning, AWS SageMaker, Databricks, Snowflake ML, and open-source ML frameworks.
  • Define scalable architectures supporting the end-to-end machine learning lifecycle, including data ingestion, feature engineering, model training, deployment, monitoring, and governance.
  • Recommend architecture patterns based on performance, scalability, security, explainability, and operational risk requirements.
  • Establish reusable solution patterns for MLOps, model serving, feature stores, automated retraining, model monitoring, and observability.
  • Design and recommend production-ready machine learning solutions with sufficient technical depth to support engineering and data science teams through implementation.
  • Evaluate vendor platforms and ecosystem offerings for enterprise fit, long-term viability, and business value.
  • Partner with data scientists and engineering teams to operationalize machine learning models at scale.
  • Provide technical leadership on machine learning architecture, MLOps, model lifecycle management, and production deployment strategies.
  • Establish standards and best practices for model governance, observability, explainability, and responsible AI.
  • Translate complex technical concepts into clear recommendations for technical and non-technical stakeholders.
  • Assess emerging machine learning technologies and translate exploratory findings into enterprise-ready recommendations.
Basic Qualifications
  • Bachelor's degree or equivalent work experience.
  • Eight (8) or more years of experience in software engineering, machine learning engineering, data engineering, solution architecture, or related technical roles.
Preferred Skills / Experience
  • Strong foundation in machine learning, software engineering, and solution architecture.
  • Experience designing and deploying production machine learning systems in cloud environments.
  • Expertise in MLOps practices, including CI/CD pipelines, model versioning, monitoring, governance, and automated retraining.
  • Hands-on experience with machine learning platforms such as Azure Machine Learning, AWS SageMaker, Databricks, Snowflake ML, MLflow, or Kubeflow.
  • Knowledge of machine learning frameworks including PyTorch, TensorFlow, Scikit-learn, XGBoost, or similar technologies.
  • Experience architecting solutions involving feature stores, model serving, real-time inference, batch scoring, and machine learning pipelines.
  • Understanding of machine learning concepts including supervised learning, unsupervised learning, forecasting, recommendation systems, anomaly detection, and model explainability.
  • Experience making architecture decisions grounded in real-world tradeoffs including cost, performance, scalability, security, governance, and model accuracy.
  • Ability to design solutions and provide technical guidance through implementation, not purely conceptual architecture.
  • Strong communication, stakeholder alignment, and cross-functional leadership skills.
  • Familiarity with generative AI and large language models is preferred but not required.
Location Expectation

This role requires working from a U.S. Bank location three (3) or more days per week.

If there's anything we can do to accommodate a disability during any portion of the application or hiring process, please refer to ourdisability accommodations for applicants.

Benefits:

Our approach to benefits and total rewards considers our team members' whole selves and what may be needed to thrive in and outside work. That's why our benefits are designed to help you and your family boost your health, protect your financial security and give you peace of mind. Our benefits include the following:

  • Healthcare (medical, dental, vision)

  • Basic term and optional term life insurance

  • Short-term and long-term disability

  • Pregnancy disability and parental leave

  • 401(k) and employer-funded retirement plan

  • Paid vacation (from two to five weeks depending on salary grade and tenure)

  • Up to 11 paid holiday opportunities

  • Adoption assistance

  • Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law

Review our full benefits available by employment status here.

U.S. Bank is an equal opportunity employer. We consider all qualified applicants without regard to race, religion, color, sex, national origin, age, sexual orientation, gender identity, disability or veteran status, and other factors protected under applicable law.

E-Verify

U.S. Bank participates in the U.S. Department of Homeland Security E-Verify program in all facilities located in the United States and certain U.S. territories. The E-Verify program is an Internet-based employment eligibility verification system operated by the U.S. Citizenship and Immigration Services. Learn more about theE-Verify program.

The salary range reflects figures based on the primary location, which is listed first. The actual range for the role may differ based on the location of the role. In addition to salary, U.S. Bank offers a comprehensive benefits package, including incentive and recognition programs, equity stock purchase 401(k) contribution and pension (all benefits are subject to eligibility requirements). Pay Range: $139,230.00 - $163,800.00

U.S. Bank will consider qualified applicants with arrest or conviction records for employment. U.S. Bank conducts background checks consistent with applicable local laws, including the Los Angeles County Fair Chance Ordinance and the California Fair Chance Act as well as the San Francisco Fair Chance Ordinance. U.S. Bank is subject to, and conducts background checks consistent with the requirements of Section 19 of the Federal Deposit Insurance Act (FDIA). In addition, certain positions may also be subject to the requirements of FINRA, NMLS registration, Reg Z, Reg G, OFAC, the NFA, the FCPA, the Bank Secrecy Act, the SAFE Act, and/or federal guidelines applicable to an agreement, such as those related to ethics, safety, or operational procedures.

Applicants must be able to comply with U.S. Bank policies and procedures including the Code of Ethics and Business Conduct and related workplace conduct and safety policies.

Posting may be closed earlier due to high volume of applicants.

What U.S. Bank employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About U.S. Bank

Sourced by ZipRecruiter

U.S. Bank is a reputable and established financial institution that plays a significant role in the banking sector. With a history spanning over 150 years, U.S. Bank has built a strong foundation of trust and reliability. As a comprehensive bank, they offer a wide array of financial products and services to cater to the diverse needs of their customers, including individuals, businesses, and communities. Customer satisfaction is of utmost importance to U.S. Bank. They prioritize delivering exceptional service and fostering long-term relationships with their clients. Through their extensive network of branches and advanced digital banking platforms, U.S. Bank ensures convenient access to their services, empowering customers to manage their finances efficiently and securely.

Industry

Banking and credit intermediation

Company size

10,000+ Employees

Headquarters location

Minneapolis, MN, US

Year founded

1863

Social media

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