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Freelance Ai Data Labeling Jobs in Michigan (NOW HIRING)

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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Freelance Ai Data Labeling information

What is freelance AI data labeling?

Freelance AI data labeling involves working independently to annotate or tag data, such as images, text, audio, or video, to help train artificial intelligence and machine learning models. Freelancers are hired by companies or platforms to manually identify and categorize data so that algorithms can learn to recognize patterns and make accurate predictions. This work is essential for improving the accuracy and performance of AI systems in various applications, including self-driving cars, voice assistants, and content moderation. Typically, freelancers need attention to detail, basic technical skills, and sometimes domain-specific knowledge, depending on the project's requirements.

What are the key skills and qualifications needed to thrive as a freelance AI data labeler?

To thrive as a Freelance AI Data Labeler, you need strong attention to detail, basic understanding of machine learning concepts, and the ability to follow complex guidelines accurately, usually supported by a high school diploma or higher education. Familiarity with data annotation platforms, labeling tools (like Labelbox or Supervisely), and sometimes specific domain knowledge is often required. Excellent time management, reliability, and clear communication help freelancers stand out in delivering high-quality, consistent results. These skills ensure that labeled data is accurate and reliable, directly impacting the effectiveness of AI models and client satisfaction.

What are some typical challenges faced by freelance AI data labelers, and how can they be managed?

Freelance AI data labelers often encounter challenges such as maintaining accuracy while working with large volumes of repetitive data, understanding complex labeling guidelines, and managing tight deadlines across multiple clients. Effective strategies include regularly reviewing project instructions, using productivity tools to track progress, and seeking clarification from clients when uncertainties arise. Maintaining open communication with project managers and participating in feedback sessions can also help improve labeling quality and efficiency.

What is the difference between Freelance Ai Data Labeling vs Data Annotation Specialist?

AspectFreelance Ai Data LabelingData Annotation Specialist
CredentialsNone required, but familiarity with labeling tools helpsOften requires training or certification in annotation tools
Work EnvironmentRemote, flexible freelance projectsTypically employed by companies or agencies, sometimes remote
Employer & IndustryFreelance platforms, AI/ML industryTech companies, AI development teams
Search & Comparison IntentLooking for freelance labeling jobsSeeking full-time or contract annotation roles

Freelance Ai Data Labeling involves independently completing labeling tasks for various clients, offering flexibility and project-based work. Data Annotation Specialists often work within organizations or agencies, focusing on detailed annotation tasks as part of a team. Both roles require knowledge of labeling tools, but freelancers typically have more varied projects, while specialists may have more structured employment settings.

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

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

What are popular job titles related to Freelance Ai Data Labeling jobs in Michigan?

For Freelance Ai Data Labeling jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Freelance Ai Data Labeling jobs in Michigan look for?

The top searched job categories for Freelance Ai Data Labeling jobs in Michigan are:

What cities in Michigan are hiring for Freelance Ai Data Labeling jobs?

Cities in Michigan with the most Freelance Ai Data Labeling job openings:

Senior Robotics Data Engineer - Only W2

Saransh Inc

Warren, MI • On-site

$99K - $135K/yr

Contractor

Re-posted 15 days ago


Job description

Role: Senior Robotics Data Engineer
Location: Warren, MI (Onsite from Day 1)
Job Type: W2 Contract
 
Main Skills: Senior Robotics Data Engineer (ML/AI systems, Python, TensorFlow and/or PyTorch, Power BI, Azure data services)
 
Key Responsibilities:
· Design and implement scalable data pipelines for large-scale robotic datasets (vision, depth, tactile, force/torque).
· Build infrastructure for high-throughput data capture from real robots and simulation environments.
· Develop and deploy semi-supervised/self-supervised data labeling workflows to minimize manual annotation costs.
· Enable simulation-to-real (Sim2Real) data workflows, including domain randomization and synthetic data generation.
· Manage data versioning, metadata, and dataset governance to support model training, evaluation, and regression testing.
· Collaborate with Robotics Perception, Grasping AI, and Simulation teams to define data requirements and KPIs.
· Establish data quality metrics that correlate with perception and grasping performance.
 
Required Qualifications:
· Minimum 3 years of experience in data engineering, machine learning systems, robotics, or related fields.
· Master’s degree in Engineering, Computer Science, Data Science, or equivalent practical experience.
· Proven experience building production-grade data pipelines for ML/AI systems.
· Strong hands-on experience with Python-based data tooling.
· Experience working with large, complex, multimodal datasets.
 
Preferred Qualifications:
· Direct experience supporting robotics perception, grasping, or manipulation 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 of TensorFlow and/or PyTorch from a data systems perspective.
· Experience with Microsoft data ecosystems (Power BI, Azure data services).