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Full Time Machine Learning Data Annotation Jobs in Detroit, MI

Lead Machine Learning Engineer

Ann Arbor, MI · On-site

$100K - $132K/yr

Provide technical leadership and mentorship to engineers and data scientists. * Translate business ... Develop and operationalize machine learning and Generative AI solutions that support business ...

Lead Machine Learning Engineer

Ann Arbor, MI · On-site

$100K - $132K/yr

Provide technical leadership and mentorship to engineers and data scientists. * Translate business ... Develop and operationalize machine learning and Generative AI solutions that support business ...

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Design, build, and maintain secure, scalable data pipelines that support reporting, analytics, and machine learning initiatives * Develop and optimize ETL/ELT processes to ingest, transform, and ...

Develop within the full machine learning lifecycle; from problem definition to data pipeline design, model development, validation, deployment, and monitoring. * Establish and refine best practices ...

Senior Machine Learning Engineer

Detroit, MI · On-site +1

$126K - $180K/yr

Develop within the full machine learning lifecycle; from problem definition to data pipeline design, model development, validation, deployment, and monitoring. * Establish and refine best practices ...

Showing results 21-40

Full Time Machine Learning Data Annotation information

See Detroit, MI salary details

$37.1K

$121.5K

$194.5K

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

As of Sep 3, 2026, the average yearly pay for full time machine learning data annotation in Detroit, MI is $121,507.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,500.00 and $134,600.00 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 popular job titles related to Full Time Machine Learning Data Annotation jobs in Detroit, MI?

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

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

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

Infographic showing various Full Time Machine Learning Data Annotation job openings in Detroit, MI as of July 2026, with employment types broken down into 19% Full Time, 7% Part Time, 68% Contract, and 6% Nights. Highlights an 4% Physical, and 96% Remote job distribution, with an average salary of $121,507 per year, or $58.4 per hour.

Full-time

Posted 20 days ago


Henry Ford Health rating

6.9

Company rating: 6.9 out of 10

Based on 573 frontline employees who took The Breakroom Quiz

454th of 898 rated healthcare providers


Job description

GENERAL SUMMARY: 

The Data Scientist, Healthcare Analytics assists the Senior Data Scientist, Healthcare Analytics and other business analysts with working with business users to fully understand their needs for data science solutions. Works with a variety of data sources, both internal and external, big and small, structured and unstructured formats to build analytic models utilizing machine-learning techniques. Partners with the IT group to ensure that the data is sourced from the right location for data science model building. Participates in the development of project deliverables, especially documentation, for data science deliverables. As a team player, interacts with various other roles such as data engineers, business analysts and others. The Data Scientist, Healthcare Analytics solves analytical problems and develops cutting edge solutions to business problems. Should also be skilled at extracting, transforming, and analyzing data using a variety of common analytical tools and statistical techniques. Should be able to present findings in a compelling manner to both a business and non-technical audience. The position requires a team player that is eager to continue to learn and evolve with business needs and changes in the data and business environment. 

EDUCATION/EXPERIENCE REQUIRED: 

  • Must have an undergraduate (BS) degree in Statistics, Mathematics, Econometrics, Operations Research, Public Health, and Epidemiology or another related field. MS degree is preferred. 
  • Three plus (3+) years of professional work experience. 
  • Two plus (2+) years of experience involving quantitative data analyses for problem solving in US Healthcare industry. 
  • Two plus (2+) years of experience with predictive, forecasting, and optimization problem solving using data analytics tools like Python, R or SAS. 
  • Exposure of working with cloud Big Data Stack to orchestrate data gathering, cleansing, preparation and modelling preferred. 
  • Advanced SQL skills working with RDBMSs such as Oracle, SQL Server, etc. 
  • Experience working with data visualization tools or Data Visualization Designers in Tableau or Power BI. 
  • Also, experience with data visualization for analytic models in Rshiny, GGPlot, Qlik, Alteryx, Flask, D3, etc. used to tell the data story to business users to foster adoption of analytic outputs created preferred. 
  • Exceptionally skilled in machine learning, data analytics, pattern recognition and predictive modelling.
  •  Strong communication and presentation skills. Effective communication and storytelling skills. 
  • Energy and enthusiasm. Passion for learning and contributing to development. A true team player. Collaborative mindset for effective communication across teams.

What Henry Ford Health employees say

Pay

Benefits

Hours and flexibility

Workplace

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About Henry Ford Health

Sourced by ZipRecruiter

Henry Ford Health provides a full continuum of services from Primary and Preventative care, to Complex and Cpecialty care, Health Insurance, a full suite of home health offerings, Virtual care, Pharmacy, Eye care and other Healthcare retail. It is one of the Nation’s leading Academic Medical Centers, recognized for Clinical excellence in Cancer care, Cardiology and Cardiovascular Surgery, Neurology and Neurosurgery, Orthopedics and Sports medicine, and Multi organ transplants. Consistently ranked among the top five NIH funded institutions in Michigan, Henry Ford Health engages in more than 2,000 research projects annually. Equally committed to educating the next generation of Health Professionals, Henry Ford Health trains more than 4,000 Medical students, Residents and fellows every year across 50+ accredited programs. With more than 33,000 valued team members, Henry Ford Health is also among Michigan’s largest and most Diverse employers, including nearly 6,000 physicians and researchers from the Henry Ford Medical Group, Henry Ford Physician Network and Jackson Health Network.

Industry

Health care and social assistance

Company size

10,000+ Employees

Headquarters location

Detroit, MI, US

Year founded

1915