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Hourly 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 ...

Judge Group, Inc.

AI Specialist

Pontiac, MI · On-site

$60 - $65/hr

Pontiac, MI Salary: $60.00 USD Hourly - $65.00 USD Hourly Description: Job Title: AI Specialist ... Big Data: Apache Spark, Databricks * Cloud: AWS (SageMaker, EC2, S3), Azure Machine Learning, Azure ...

Judge Group, Inc.

Midlevel AI Developer

Ann Arbor, MI · On-site

$50 - $55/hr

Ann Arbor, MI Salary: $50.00 USD Hourly - $55.00 USD Hourly Description: Our client is currently ... Bachelor's degree in Computer Science, Software Engineering, Data Science, a related field, or ...

Mercor

Mechanical Engineer - AI Trainer

Detroit, MI · Remote

$70 - $110/hr

Collaborate with AI research teams to enhance training data quality and downstream performance ... Qualified experts will be paid hourly for the remainder of the project. Application Process (Takes ...

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Hourly Ai Data Annotation information

What is an hourly AI data annotation?

An Hourly AI Data Annotation job involves labeling, tagging, or categorizing data—such as images, text, or audio—to help train machine learning models. Annotators follow specific guidelines to ensure that the data is accurately labeled so that AI systems can learn to recognize patterns and make decisions. These jobs are typically paid by the hour and may require attention to detail, consistency, and sometimes familiarity with specialized annotation tools. This work is essential for improving the accuracy and usefulness of artificial intelligence applications.

What are the key skills and qualifications needed to thrive as an hourly AI data annotator?

To thrive as an AI Data Annotator, you need strong attention to detail, accuracy, and a basic understanding of data labeling concepts, typically supported by a high school diploma or equivalent. Familiarity with annotation tools such as Labelbox or Supervisely, and basic computer proficiency, are often required. Critical thinking, consistency, and effective communication are valuable soft skills in this role. These skills ensure high-quality, reliable data that directly improves the performance of AI and machine learning models.

What are some common challenges faced by hourly AI data annotators, and how can they be managed?

Hourly AI data annotators often encounter challenges such as repetitive tasks, maintaining high accuracy under time constraints, and adapting to evolving project guidelines. To manage these, it's important to take regular breaks to avoid fatigue, stay up to date with training materials, and communicate proactively with team leads if instructions are unclear. Many teams use collaborative tools and regular feedback sessions to support annotators and ensure consistent quality, making teamwork and attention to detail vital for success in this role.

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

AspectHourly Ai Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or in-office, flexible hoursRemote or in-office, flexible hours
Industry UsageAI, machine learning, tech companiesAI, machine learning, tech companies
Job FocusAnnotating data for AI training, often with specific instructionsLabeling data to help AI models learn, often similar tasks

Hourly Ai Data Annotation and Data Labeler roles are similar, focusing on preparing data for AI systems. The main difference lies in terminology; 'Hourly Ai Data Annotation' emphasizes the paid hourly aspect and the specific task of annotating data for AI training, while 'Data Labeler' is a broader term used interchangeably in the industry. Both roles require similar skills and are used in the same industry sectors.

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:

What are popular job titles related to Hourly Ai Data Annotation jobs in Michigan?

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

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

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

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

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

Hourly Ai Data Annotation jobs near you

Senior Robotics Data Collection Engineer - Only W2

Warren, MI • On-site

Saransh Inc
IT Services • 51 - 200 employees
Learn more about Saransh Incexternal

$99K - $135K/yr

Contractor

Re-posted 21 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.