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Weekend Ai Data Annotation Jobs in Michigan (NOW HIRING)

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.

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.

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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Weekend Ai Data Annotation information

What is a Weekend AI Data Annotation specialist?

Weekend AI Data Annotators are professionals who label, categorize, and tag data—such as images, audio, or text—for use in training artificial intelligence models, specifically working on weekends. Their work ensures that machine learning algorithms receive high-quality, accurately labeled datasets for tasks like computer vision, natural language processing, or speech recognition. This role often involves using specialized annotation tools and following precise guidelines to maintain consistency and accuracy. Weekend annotators may work remotely or on-site, and their contributions are vital for improving AI system performance.

What are common challenges faced by Weekend AI Data Annotation specialists, and how can they be managed?

Weekend AI Data Annotation specialists often encounter challenges such as maintaining high attention to detail during repetitive tasks and managing productivity over long annotation sessions. Since the work is typically remote or semi-remote, self-motivation and effective time management are crucial to meet project deadlines. It's helpful to take regular breaks, communicate proactively with team leads when questions arise, and make use of any annotation guidelines or quality assurance feedback provided. Collaborating with teammates through chat platforms or project management tools can also enhance consistency and resolve uncertainties quickly.

How much do you get paid for AI data annotation?

The pay for AI data annotation jobs varies depending on the employer, project complexity, and experience level, but typically ranges from $10 to $20 per hour or $0.02 to $0.10 per task. Many roles are paid on a per-task basis, and some may offer bonuses for accuracy or speed. Compensation can also depend on whether the work is freelance or employed by a company.

What skills and qualifications are needed to thrive as a Weekend AI Data Annotation specialist?

To thrive as a Weekend AI Data Annotation Specialist, you need attention to detail, strong analytical skills, and familiarity with data labeling processes, often supported by a high school diploma or post-secondary coursework in a technical field. Proficiency with annotation platforms like Labelbox, Supervisely, or internal company tools is typically required, along with basic knowledge of data privacy protocols. Reliability, time management, and effective communication are crucial soft skills for meeting project deadlines and collaborating with remote teams. These skills and qualities ensure the accuracy and efficiency of annotated datasets, which are essential for high-performing AI systems.
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Weekend 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 29 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.