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Internship Ai Data Annotation Jobs in Michigan (NOW HIRING)

micro1 AI

AI Trainer - Microbiology Expert

Detroit, MI · Remote

$70 - $90/hr

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

micro1 AI

AI Trainer - Microbiology Expert

Dearborn, MI · Remote

$70 - $90/hr

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

micro1 AI

AI Trainer - Microbiology Expert

Warren, MI · Remote

$70 - $90/hr

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

micro1 AI

AI Trainer - Microbiology Expert

Lansing, MI · Remote

$70 - $90/hr

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

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 ...

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Internship Ai Data Annotation information

What is an AI data annotation internship?

An AI Data Annotation Internship is a temporary position where interns help label, tag, or categorize data (such as images, text, or audio) to train and improve artificial intelligence models. Interns typically work with datasets, ensuring that the information provided is accurate and consistent, which is crucial for machine learning algorithms to learn effectively. The role is a valuable entry point for those interested in AI, machine learning, or data science, as it offers hands-on experience with the foundational work needed to build intelligent systems.

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

To thrive as an Internship AI Data Annotation specialist, you need attention to detail, basic computer literacy, and a foundational understanding of data labeling concepts, often supported by ongoing training or coursework in data science or computer science. Familiarity with annotation tools like Labelbox, Supervisely, or VIA, and knowledge of data management platforms are commonly required. Strong organizational skills, patience, and effective communication help you manage repetitive tasks and collaborate with team members. These skills are essential to ensure high-quality data labeling, which directly impacts the performance and accuracy of AI models.

What are the typical challenges faced during an AI data annotation internship, and how can I overcome them?

As an AI Data Annotation intern, you may encounter challenges such as maintaining high accuracy while labeling large volumes of data, understanding complex annotation guidelines, and adapting to evolving project requirements. It's important to regularly communicate with your team lead or project manager to clarify any uncertainties and ensure consistency in your annotations. Leveraging available training materials and asking for feedback will help you improve your efficiency and accuracy, turning these challenges into valuable learning experiences.

What is the difference between Internship Ai Data Annotation vs Data Labeler?

AspectInternship Ai Data AnnotationData Labeler
CredentialsHigh school diploma or equivalent; some roles prefer basic technical skillsHigh school diploma or equivalent; minimal formal education required
Work EnvironmentOffice or remote; supervised tasks, often part-time or temporaryOffice or remote; repetitive tasks, often entry-level
Industry UsageTech companies, AI startups, research projectsTech firms, data companies, AI development teams
Search & Comparison IntentUnderstanding entry-level roles in AI data annotationComparing entry-level data labeling jobs in AI

Internship Ai Data Annotation roles typically involve supervised, short-term tasks aimed at gaining experience in AI data preparation. Data Labeler positions are similar entry-level roles focused on labeling data for machine learning. Both roles require basic skills and are used across tech and AI industries, but internships often offer more training and learning opportunities.

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 Internship Ai Data Annotation jobs in Michigan, the most frequently searched job titles are:

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Internship Ai Data Annotation jobs near you

Senior Robotics Data Collection Engineer - Only W2

Saransh Inc

Warren, MI • On-site

$99K - $135K/yr

Contractor

Re-posted 12 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.