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Contract Data Labeler Jobs in Michigan (NOW HIRING)

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Contract Data Labeler information

What is the difference between Contract Data Labeler vs Data Annotator?

AspectContract Data LabelerData Annotator
CredentialsHigh school diploma or equivalent; basic computer skillsHigh school diploma or equivalent; attention to detail
Work EnvironmentRemote or on-site; tech companies, AI firmsRemote or on-site; AI and machine learning projects
Industry UsageUsed in AI training, machine learning datasetsUsed in AI, computer vision, NLP projects
Job FocusLabeling data for machine learning modelsAnnotating data to improve AI algorithms

The Contract Data Labeler and Data Annotator roles are similar, both involve labeling data for AI training. The main difference lies in terminology and specific project focus, but they often share similar credentials, work environments, and industry applications.

What are the key skills and qualifications needed to thrive as a Contract Data Labeler, and why are they important?

To thrive as a Contract Data Labeler, you need strong attention to detail, accuracy, and basic data management skills, often supported by a high school diploma or equivalent. Familiarity with data annotation tools, spreadsheet software, and sometimes project management platforms is typically required. Excellent focus, time management, and the ability to follow detailed instructions are crucial soft skills in this role. These skills ensure labeled data is reliable and consistent, which is vital for training high-quality AI and machine learning models.

What are some common challenges faced by Contract Data Labelers, and how can they be addressed?

Contract Data Labelers often work with large volumes of diverse data, which can lead to repetitive tasks and fatigue. Ensuring accuracy and consistency in labeling is crucial, as errors can significantly impact machine learning outcomes. To address these challenges, it's important to take regular breaks, follow detailed guidelines, and communicate with team members or project leads when ambiguities arise. Many teams use quality assurance checks and feedback sessions to help labelers maintain high standards and continuously improve their work.

What are contract data labelers?

Contract data labelers are professionals hired on a temporary or project basis to annotate and categorize data, such as images, text, or audio, for use in machine learning and artificial intelligence projects. Their main responsibility is to accurately tag or label data according to specific guidelines so that algorithms can learn to recognize patterns. As contractors, they typically work remotely and are paid per task, hour, or project. This role is essential for companies developing AI models that require large sets of accurately labeled data.
What are the most commonly searched types of Data Labeler jobs in Michigan? The most popular types of Data Labeler jobs in Michigan are:
What are popular job titles related to Contract Data Labeler jobs in Michigan? For Contract Data Labeler jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Contract Data Labeler jobs in Michigan look for? The top searched job categories for Contract Data Labeler jobs in Michigan are:
Contract Data Labeler jobs near you

Senior Robotics Data Engineer - Only W2

Saransh Inc

Warren, MI • On-site

$99K - $135K/yr

Contractor

Re-posted 9 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).