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Full Time Machine Learning Data Annotation Jobs in Minneapolis, MN

Machine Learning Engineer

Minneapolis, MN ยท On-site

$85K - $125K/yr

Machine learning experience using visual data * Understanding of a variety of machine learning ... Some travel is required, typically 5-25% * Full-time on-site work at the Kitware Office Preferred ...

Machine learning experience using visual data * Understanding of a variety of machine learning ... Some travel is required, typically 5-25% * Full-time on-site work at the Kitware Office Preferred ...

Machine learning experience using visual data * Understanding of a variety of machine learning ... Some travel is required, typically 5-25% * Full-time on-site work at the Kitware Office Preferred ...

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

GCP ML Architect - Data

Chaska, MN ยท 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 ...

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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 Jul 5, 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 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 are Full Time Machine Learning Data Annotation jobs?

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 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 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:
Machine Learning Engineer

Machine Learning Engineer

Kitware

Minneapolis, MN โ€ข On-site

$85K - $125K/yr

Full-time

Medical, Life, Retirement, PTO

Posted 26 days ago


Job description

Team Description:
Kitware is a leader in advanced research and algorithm development in artificial intelligence (AI), spanning computer vision (CV), natural language processing (NLP), vision-language models (VLMs), and other generative AI technologies. Our solutions embracing AI add measurable value to government agencies, commercial organizations, and academic institutions worldwide. We have developed a deep understanding in extracting useful, actionable information from multiple data sources like images, video, metadata, audio, and text, and we recognize the need for robust, affordable solutions. We seek to advance AI, CV, and other related fields through research and development and collaborative projects that can contribute to our open source software platforms, such as XAITK, NRTK, and GeoWATCH.
About the Projects:
Kitware's employees have unique opportunities to interact and collaborate directly with customers, visit interesting customer sites, and participate in live field tests and demonstrations. Much of Kitware's work involves applying state-of-the-art artificial intelligence approaches to dynamic, real-world problems. We consider the work that we do on our government contracts as one of the ways that we give back to the community. We partner with premier government R&D agencies such as DARPA, IARPA, AFRL, Army C5ISR, NOAA, and other branches of the US Government on a range of efforts, including prime contracts, SBIRs, and STTRs. In addition, we provide commercial services to companies ranging from startups to Fortune 500 companies. Kitware employs an open source business model to foster extended, collaborative communities and to provide effective, flexible, and high-quality technical solutions.
In This Position You Will:
  • Collaborate with researchers on projects related to machine learning, artificial intelligence, and computer vision
  • Perform rapid prototyping and enhanced development to be integrated into operational systems
  • Contribute your strong programming ability and experience to develop robust solutions for real-world problems
  • Validate, optimize, and deploy advanced exploitation algorithms
  • Perform troubleshooting, bug fixes, and maintenance of existing and new code to ensure stability and robustness

Required Qualifications:
  • Bachelor's degree or Master's degree in Computer Science, Electrical and Computer Engineering, or related field
  • Proficiency in Python
  • Experience with deep learning libraries (PyTorch, TensorFlow, etc.)
  • Strong background in both classical and modern (deep learning) machine learning, including model selection, architecting, training, validation, testing, and deployment
  • Machine learning experience using visual data
  • Understanding of a variety of machine learning tasks, e.g. Object Detection, Segmentation, Re-Identification, Tracking, Pose, Super Resolution, Natural Language Processing
  • A high level of comfort with academic literature and the ability to adapt research products to solve real-world problems
  • Due to contractual requirements, only US Citizens will be considered for this position
  • If not already cleared TS/SCI, willingness and ability to apply for and maintain a TS/SCI security clearance
  • Some travel is required, typically 5-25%
  • Full-time on-site work at the Kitware Office

Preferred Qualifications:
  • Active SECRET, TS, or TS/SCI security clearance
  • Experience curating quality, real-world datasets for training deep learning models
  • Proficiency in C++

$85,000 - $125,000 a year
Company Description:
Kitware is a research and development software solutions provider with a mission to advance science, make a positive impact, and share our results all within a collaborative, employee-focused work environment that is friendly, fair, and flexible. Our work is improving healthcare outcomes, increasing national security, and advancing our national computing infrastructure. Our customers and collaborators include top universities from around the world, government organizations, national research labs, medical device manufacturers, car manufacturers, financial institutions, and many others.
Kitware is proud to be 100% employee-owned, and Great Place to Work-Certifiedโ„ข.
Additional Information:
Our team members enjoy a small company environment, flexibility in work assignments, and high levels of independence and responsibility. Besides a great work environment, our comprehensive benefits package includes a competitive compensation plan, tuition reimbursement program, flexible working hours, six weeks paid time off, 401(k), health insurance, life insurance, short- and long-term disability insurance, bonus plan, and free coffee, drinks, and snacks.
For more information on our benefit offerings please visit: https://www.kitware.com/careers/.
Kitware actively subscribes to a policy of equal employment opportunity. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, age, protected veteran status, uniformed service member status, or any other characteristics protected by applicable law.
Any unsolicited resume sent to Kitware, including to Kitware's mailing addresses, fax machines or email addresses, whether directly to Kitware employees or to Kitware's applicant tracking system, will be considered Kitware property. Kitware will not pay a fee for any placement resulting from the receipt of an unsolicited resume, and will consider any candidate submitted by a recruitment agency without a fully executed contract with Kitware to have been referred free of any charges or fees.
If you need assistance with applying or interviewing for a role due to a disability or special need, please reach out directly to our HR team at [email protected] at any time during the hiring process.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.