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Data Annotation Engineer Jobs in Michigan (NOW HIRING)

Torc Robotics

Senior, ML Engineer - VLM

Ann Arbor, MI · On-site

$102K - $140K/yr

Mentors and guides engineers within the group. * Bachelor's Degree in Computer Science, Robotics ... data engines for annotation and verification. * High-throughput model serving - vLLM, SGLang, or ...

Torc Robotics

Senior, ML Engineer - VLM

Ann Arbor, MI · On-site +1

$102K - $140K/yr

Mentors and guides engineers within the group. * Bachelor's Degree in Computer Science, Robotics ... data engines for annotation and verification. * High-throughput model serving - vLLM, SGLang, or ...

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Showing results 1-20

All JobsData Annotation Engineer JobsData Annotation Engineer Jobs in Michigan

Data Annotation Engineer information

See Michigan salary details

$44.9K

$128.5K

$171.7K

How much do data annotation engineer jobs pay per year?

As of Jul 30, 2026, the average yearly pay for data annotation engineer in Michigan is $128,526.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,200.00 and $170,800.00 per year, depending on experience, location, and employer.

What are the main challenges faced by Data Annotation Engineers in their daily work?

One of the main challenges Data Annotation Engineers face is ensuring consistent accuracy and quality in labeling large and often complex datasets. Attention to detail is critical, as even small errors can significantly affect machine learning model performance. Additionally, engineers must frequently adapt to evolving annotation guidelines and emerging data types, which requires ongoing learning and flexibility. Collaboration with data scientists and project managers is common to clarify requirements and resolve ambiguities, making strong communication skills essential for success.

What are the key skills and qualifications needed to thrive in the Data Annotation Engineer position, and why are they important?

To thrive as a Data Annotation Engineer, you need a strong background in data analysis, attention to detail, and familiarity with annotation processes, often supported by a degree in computer science or a related field. Proficiency with annotation tools like Labelbox, CVAT, or VIA, and understanding of data formats used in machine learning, is commonly required. Excellent communication, collaboration, and organizational skills help you effectively manage projects and cooperate with cross-functional teams. These abilities are crucial for delivering high-quality labeled data, which directly impacts the performance of AI and machine learning models.

Does data annotation really pay?

Data annotation engineers can earn competitive wages, often paid hourly or per task, with pay rates varying based on experience, complexity of annotations, and the platform or employer. Entry-level roles may start at minimum wage, while experienced annotators or those with specialized skills can earn higher salaries or freelance rates. Overall, data annotation can provide a reliable income, especially for remote or flexible work arrangements.

What is the highest salary for data annotator?

The highest salary for a data annotation engineer can reach up to $80,000 to $100,000 annually, depending on experience, location, and the complexity of annotation tasks. Senior roles or those with specialized skills in tools like Labelbox or CVAT may earn higher compensation. Salaries vary widely across companies and regions but generally reflect the technical skills required for high-quality data labeling.

What is a data annotation engineer?

A data annotation engineer is a professional responsible for labeling and annotating data, such as images, text, or videos, to prepare it for machine learning models. They often use specialized tools and follow guidelines to ensure data quality, supporting the development of AI systems.

How hard is it to get hired by data annotation?

Getting hired as a data annotation engineer typically requires basic computer skills, attention to detail, and familiarity with annotation tools. Many positions are entry-level and may not require advanced degrees, but strong accuracy and consistency are important for success in the role.

What is a Data Annotation Engineer job?

A Data Annotation Engineer is responsible for labeling and annotating data—such as text, images, audio, or video—to train machine learning models. They ensure that data is accurately categorized and structured to improve model performance. This role often involves using specialized annotation tools, following detailed guidelines, and working closely with data scientists and AI teams. Data Annotation Engineers play a crucial role in the development of AI applications by providing high-quality labeled datasets for supervised learning.

What are popular job titles related to Data Annotation Engineer jobs in Michigan? For Data Annotation Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Data Annotation Engineer jobs in Michigan look for? The top searched job categories for Data Annotation Engineer jobs in Michigan are:
What cities in Michigan are hiring for Data Annotation Engineer jobs? Cities in Michigan with the most Data Annotation Engineer job openings:
Data Annotation Engineer jobs near you
Infographic showing various Data Annotation Engineer job openings in Michigan as of July 2026, with employment types broken down into 68% Full Time, 13% Part Time, and 19% Contract. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $128,526 per year, or $61.8 per hour.

Robotics Data Collection Engineer

Nastech Global

Warren, MI • On-site

Contractor

Re-posted 8 hours ago

Job description

Position: Robotics Data Collection Engineer

Location: Warren, Michigan (Onsite)

Duration: 12+Months with possible extensions

Main Skills: Senior Robotics Data Collection Engineer (MLE, Python, Cloud exp, Linux)

Position Summary:

Join Automation, Robotics & Controls (ARC) AI team as a Robotics Data Collection Engineer. In this hands-on role, you will work directly with advanced robotic systems to collect, organize, and validate training data that enables AI-powered robotic manipulation in automotive manufacturing. You will contribute to building the datasets that power the next generation of intelligent manufacturing automation at Warren Technical Center.

Key Responsibilities:

  • Collect high-quality robot telemetry, sensor, and visual data from manufacturing robotic systems in lab and production-like environments.
  • Operate and monitor robotic systems, GELLO teleop interfaces, and data collection hardware.
  • Organize, label, and validate data according to established annotation guidelines and quality standards.
  • Perform manual annotation and verification when necessary to generate high-quality ground truth labels.
  • Execute data collection campaigns following documented protocols and experimental designs.
  • Troubleshoot data collection issues and document problems for engineering teams.
  • Collaborate with AI engineers, robotics engineers, and manufacturing teams to ensure data meets model training requirements.

Required Qualifications:

  • College or bachelor’s degree in engineering (Mechanical Engineering or Electrical Engineering preferred).
  • Ability to work on-site at Warren Technical Center, 5 days per week.
  • Attention to detail and ability to follow technical procedures and documentation.
  • Reliability, accountability, and ability to work independently and as part of a team.
  • Strong, demonstrated hands-on experience operating, troubleshooting, and maintaining industrial or collaborative robotic arms.
  • Proficiency in Linux environments and basic scripting (e.g., Python) to interface with robotic systems and manage data pipelines.
  • Proven experience working directly with perception sensors and hardware, with a solid understanding of capturing and validating high-quality sensor data.

Preferred Qualifications:

  • Experience with robotics, manufacturing, or data collection.
  • Familiarity with Python, Linux, or data tools (beneficial but not required).
  • Experience operating or troubleshooting technical equipment.
  • Basic understanding of machine learning, AI, or data annotation concepts.
  • Experience in automotive or manufacturing environments.

What is Offered:

•              Hands-on experience with cutting-edge robotics and AI technology.

•              Opportunity to contribute to transformative manufacturing automation.

•              Collaborative team environment with world-class engineers and researchers.