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Entrylevel Ai Data Labeling Jobs in Michigan (NOW HIRING)

Saransh Inc

Senior Robotics Data Engineer - Only W2

Warren, MI · On-site

$99.60K - $135.20K/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 ...

Accenture

Data Protection Sr. Analyst

Detroit, MI · Hybrid

$84.80K - $100.70K/yr

... labels/encryption, DLP policies, data classification/discovery, Insider Risk Management ... Contribute to emerging areas such as AI and agentic AI security, under guidance. . Qualifications ...

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Entrylevel Ai Data Labeling information

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

AspectEntrylevel Ai Data LabelingData Annotation Specialist
CredentialsBasic computer skills, no formal certification often requiredSimilar; basic skills, sometimes certifications in data management
Work EnvironmentRemote or on-site, repetitive tasksRemote or on-site, similar repetitive tasks
Industry UsageCommon in AI/ML companies, tech startupsUsed across tech, healthcare, automotive industries

Both roles involve labeling data for AI training, often requiring similar skills and work environments. The main difference lies in terminology; 'Data Annotation Specialist' may imply a broader scope or more specialized tasks, but both are entry-level roles focused on preparing data for machine learning models.

What are popular job titles related to Entrylevel Ai Data Labeling jobs in Michigan? For Entrylevel Ai Data Labeling jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Entrylevel Ai Data Labeling jobs in Michigan look for? The top searched job categories for Entrylevel Ai Data Labeling jobs in Michigan are:
What cities in Michigan are hiring for Entrylevel Ai Data Labeling jobs? Cities in Michigan with the most Entrylevel Ai Data Labeling job openings:
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Infographic showing various Entrylevel Ai Data Labeling job openings in Michigan as of May 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% In-person job distribution.

Senior Robotics Data Engineer - Only W2

Saransh Inc

Warren, MI • On-site

$99.60K - $135.20K/yr

Contractor

Posted 20 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).