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Full Time Machine Learning Data Annotation Jobs in Detroit, MI

A123 Systems Corp.

Battery Modeling Engineer

Novi, MI · On-site

Develop data-driven AI machine learning models to optimize the design of battery cell manufacturing process considering the cell quality control and capital costs. * Support NBO and regular life ...

Maddisoft

AI Specialist

Rochester, MI · On-site

The ideal candidate will possess a strong background in machine learning, data science, AI frameworks, and cloud technologies, along with the ability to translate business challenges into scalable AI ...

Autodesk

Senior Machine Learning Test Engineer

Novi, MI · On-site +1

$103K - $134K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East ... Define ML quality strategy and acceptance criteria across data, model, and system levels * Design ...

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All JobsMachine Learning Data Annotation JobsFull Time Machine Learning Data Annotation JobsFull Time Machine Learning Data Annotation Jobs in Detroit, MI

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 Aug 14, 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 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 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 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:

Full Time Machine Learning Data Annotation jobs near you
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.

Battery Modeling Engineer

A123 Systems Corp.

Novi, MI • On-site

Full-time

Re-posted 28 days ago

Job description

A123 Systems, LLC is a leading developer and manufacturer of advanced lithium-ion battery technologies and energy storage systems. Our solutions serve a wide range of applications, from traditional automotive batteries to utility-scale and commercial & industrial (C&I) energy storage. Committed to safety, longevity, and energy efficiency, A123 delivers high-performance battery technology solutions with a strong commitment to grow and serve our customers, industry requirements with the goal to make the Air Cleaner.
Position Overview
The Advanced Simulation Technology & AI Department at A123 Systems is hiring a Battery Modeling Engineer with the major responsibilities of developing physics-based models for different cell chemistry to understand the aging mechanisms and optimize the cell design, and developing data-driven AI machine learning models to optimize battery cell manufacturing process. Other responsibilities include conducting cell-, module-, and pack-level life simulation for Li-ion battery systems used in electric vehicles, plug-in hybrid electric vehicles, hybrid electric vehicles, energy storage systems, drone and electric vertical take-off and landing.
Primary Responsibilities
  • Develop physics-based models to identify aging mechanisms and optimize cell design.
  • Develop data-driven AI machine learning models to optimize the design of battery cell manufacturing process considering the cell quality control and capital costs.
  • Support NBO and regular life simulation activities through global collaboration.
  • Work in a global team and collaborate with cross-functional team colleagues.
  • Communicate findings to external customers in a positive and constructive manner, and establish/maintain technical communications for any open issues.

Specific Skills/Experience
  • Solid knowledge of electrochemical modeling and battery aging.
  • Solid Knowledge of battery chemistry and battery manufacturing.
  • Excellent experience in modeling of electrochemical systems.
  • Solid knowledge of machine learning, data cleaning, cloud computing, etc.
  • Sophisticated software/programming skills, such as COMSOL, Matlab, Python, etc.
  • Experience with ML libraries, i.e., Tensor Flow, PyTorch, etc.
  • Experience in Li-ion battery modeling and machine learning in industry is a plus.
  • Strongly self-motivated and willingness to learn new knowledge.
  • 0-2 years industry working experience.

Education
  • Ph.D. degree in Engineering, Physics, Math, Statistics, Analytics, etc.

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