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Entry Level Ai Data Annotation Jobs in Michigan (NOW HIRING)

Saransh Inc

Senior Robotics Data Engineer - Only W2

Warren, MI · On-site

$99K - $135K/yr

... AI. · Familiarity with robotics simulation platforms (e.g., Isaac Sim) and synthetic data generation. · Experience with data labeling tools and annotation workflows at scale. · Hands-on knowledge ...

IBM

Associate Data Engineer 2027 - AI & Analytics

Lansing, MI · On-site

$59K - $60K/yr

At IBM, AI is part of how we deliver solutions, accelerate development, analyze data, automate ... entry-level positions. You'll receive a status update email for each application, so be sure to ...

Accenture

Data Protection, A/SA-Evergreen

Detroit, MI

$84K - $100K/yr

Contribute to emerging areas such as AI and agentic AI security, under guidance. . Qualifications ... Prior internship, academic project, or entry-level experience in security or compliance is a plus.

Socket.dev

AI Software Engineer

Farmington Hills, MI · On-site

This is an entry-level position, ideal for a recent graduate or early-career engineer eager to grow ... Master's degree in Mathematics, Computer Science, Data Science, or a related field preferred. * 0 ...

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Entry Level Controls Engineer

Detroit, MI · On-site

$80K - $82K/yr

*Must be okay with travel Entry Level Position: College Graduate - 2 years experience This is a ... to AI to User Interface tools. * Provide our clients with real-time data, and actionable ...

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Entry Level Ai Data Annotation information

What is an entry level AI data annotation?

An Entry Level AI Data Annotation job involves labeling and categorizing data such as images, text, audio, or video to help train artificial intelligence (AI) and machine learning models. Annotators follow specific guidelines to tag data accurately, ensuring that AI systems learn to recognize patterns correctly. These positions typically require attention to detail, basic computer skills, and the ability to follow instructions. No advanced technical knowledge is usually required, making it a great way to start a career in the AI or tech industry.

What are the key skills and qualifications needed to thrive as an entry level AI data annotation specialist?

To thrive as an Entry Level AI Data Annotation Specialist, attention to detail, basic computer literacy, and a high school diploma or equivalent are typically required. Familiarity with data labeling platforms, annotation tools, and spreadsheet software is often expected. Strong organizational skills, focus, and the ability to work independently help individuals excel in this role. These skills ensure accurate and efficient data labeling, which is crucial for developing reliable AI and machine learning models.

What are some common challenges faced by entry level AI data annotation specialists, and how can they be addressed?

Entry-level AI data annotation specialists often encounter challenges such as maintaining consistency and accuracy while labeling large volumes of data, understanding nuanced instructions, and adapting to changing project requirements. These challenges can be addressed by actively seeking clarification from team leads, participating in training sessions, and regularly reviewing annotation guidelines. Collaborating with teammates and using quality assurance feedback also helps improve accuracy and ensures alignment with project standards.

What are the most commonly searched types of Ai Data Annotation jobs in Michigan?

The most popular types of Ai Data Annotation jobs in Michigan are:

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For Entry Level Ai Data Annotation jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Entry Level Ai Data Annotation jobs in Michigan look for?

The top searched job categories for Entry Level Ai Data Annotation jobs in Michigan are:

What cities in Michigan are hiring for Entry Level Ai Data Annotation jobs?

Cities in Michigan with the most Entry Level Ai Data Annotation job openings:

Entry Level Ai Data Annotation jobs near you
Infographic showing various Entry Level Ai Data Annotation job openings in Michigan as of August 2026, with employment types broken down into 71% Full Time, and 29% Contract. Highlights an 100% In-person job distribution.

Senior Robotics Data Collection Engineer - Only W2

Warren, MI • On-site

Saransh Inc
See more jobs at Saransh Incexternal

$99K - $135K/yr

Contractor

Re-posted 17 days ago

Job description

Role: Senior Robotics Data Collection Engineer
Location: Warren, MI (Onsite from Day 1)
Job Type: W2 Contract
 
Main Skills: Senior Robotics Data Collection Engineer (MLE, Python, Cloud exp, Linux)
 
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).
· Attention to detail and ability to follow technical procedures and documentation.
· 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.