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Entry Level Data Annotation Tech Jobs in Detroit, MI

Align Communications

Data Center Project Analyst

Detroit, MI · On-site

$119K/yr

... technologies, make an impact within the industry and acquire valuable new skills whether on client sites or in one of our regional offices. Position Overview Align seeks an Entry Level Data Center ...

Oakland Medical Group

Be Seen First

Laboratory Tech

Farmington Hills, MI · On-site

$18 - $20/hr

Record accurate data and maintain logs for laboratory activities * Conduct quality control checks ... Qualifications * Entry-level experience in laboratory techniques * High school diploma or GED

In-finite Search Solutions

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Entry Level Controls Engineer

Detroit, MI · On-site

$82K - $106K/yr

Provide our clients with real-time data, and actionable information about their facilities ... Familiarity with web development technologies * Design and Implementation of Relational/Document ...

Pwc

Data Engineer - Senior Associate

Detroit, MI · On-site

$77K - $202K/yr

In this role within our Technology Consulting practice, you will leverage advanced technologies and ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

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Entry Level Data Annotation Tech information

See Detroit, MI salary details

$11

$19

$26

How much do entry level data annotation tech jobs pay per hour?

As of Jul 24, 2026, the average hourly pay for entry level data annotation tech in Detroit, MI is $19.14, according to ZipRecruiter salary data. Most workers in this role earn between $16.20 and $21.20 per hour, depending on experience, location, and employer.

What is the difference between Entry Level Data Annotation Tech vs Entry Level Data Labeler?

AspectEntry Level Data Annotation TechEntry Level Data Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech-focusedRemote or on-site, tech-focused
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, autonomous vehicles

Both roles involve labeling data for AI training, requiring similar skills and environments. The main difference lies in terminology; 'Data Annotation Tech' emphasizes the technical aspect of annotation, while 'Data Labeler' is a more general term. Both are entry-level positions vital for AI development in tech industries.

What are some common challenges faced by Entry Level Data Annotation Techs, and how can they be managed?

Entry Level Data Annotation Techs often encounter challenges like maintaining focus during repetitive tasks, ensuring accuracy under tight deadlines, and adapting to evolving annotation guidelines. To manage these, it's helpful to take regular breaks, double-check your work, and actively seek feedback from supervisors. Collaborating with teammates and participating in training sessions can also improve both speed and consistency, making the work more manageable and rewarding.

What is an Entry Level Data Annotation Tech?

An Entry Level Data Annotation Tech is responsible for labeling and categorizing data, such as images, text, or audio, to help train machine learning models. This role typically involves using specialized software to accurately tag and classify data according to specific guidelines. It is a foundational position within the field of artificial intelligence and data science, requiring attention to detail and consistency. No advanced technical skills are usually required, making it a suitable entry point for those interested in AI or data-related careers.

What are the key skills and qualifications needed to thrive as an Entry Level Data Annotation Tech, and why are they important?

To thrive as an Entry Level Data Annotation Tech, you need strong attention to detail, basic computer literacy, and a high school diploma or equivalent. Familiarity with annotation software, data labeling platforms, and basic spreadsheet tools is typically required. Patience, consistency, and effective communication help ensure accuracy and efficient teamwork. These skills and qualities are essential for delivering high-quality labeled data that supports machine learning and AI development.
What are the most commonly searched types of Data Annotation Tech jobs in Detroit, MI? The most popular types of Data Annotation Tech jobs in Detroit, MI are:
What are popular job titles related to Entry Level Data Annotation Tech jobs in Detroit, MI? For Entry Level Data Annotation Tech jobs in Detroit, MI, the most frequently searched job titles are:
What job categories do people searching Entry Level Data Annotation Tech jobs in Detroit, MI look for? The top searched job categories for Entry Level Data Annotation Tech jobs in Detroit, MI are:
Entry Level Data Annotation Tech jobs near you

Robotics Data Collection Engineer

Nastech Global

Warren, MI • On-site

Contractor

Posted 24 days 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.