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Entry Level Ai Data Trainer Jobs in Michigan (NOW HIRING)

IntraEdge

AI Data Engineer

Detroit, MI

$113K - $136K/yr

Automate the training and deployment of AI/ML models into production via APIs and microservices. * Monitor and troubleshoot: Implement data observability tools to monitor pipeline health, identify ...

Deloitte

AI Engineer Consultant

Detroit, MI · Hybrid

You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations ... Deliver governed datasets and feature engineering/serving for ML training and real-time inference ...

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. * Collaborate with interdisciplinary teams to ensure scientific rigor and data integrity in AI development.

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. * Collaborate with interdisciplinary teams to ensure scientific rigor and data integrity in AI development.

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. * Collaborate with interdisciplinary teams to ensure scientific rigor and data integrity in AI development.

micro1 AI

AI Trainer - Microbiology Expert

Ann Arbor, MI · Remote

$70 - $90/hr

Document experimental findings and processes with a focus on clarity for AI training data. * Collaborate with interdisciplinary teams to ensure scientific rigor and data integrity in AI development.

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. * Collaborate with interdisciplinary teams to ensure scientific rigor and data integrity in AI development.

IBM

Associate Data Engineer 2027 - AI & Analytics

Lansing, MI · On-site

$59K - $60K/yr

... entry-level positions. You'll receive a status update email for each application, so be sure to ... Training and educational resources on our personalized, AI-driven learning platform where IBMers ...

New

IBM

Associate Data Engineer 2027 - AI & Analytics

Lansing, MI · On-site

$59K - $60K/yr

... entry-level positions. You'll receive a status update email for each application, so be sure to ... Training and educational resources on our personalized, AI-driven learning platform where IBMers ...

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Entry Level Ai Data Trainer information

What does an entry level AI data trainer do?

An Entry Level AI Data Trainer is responsible for preparing, labeling, and organizing data that is used to train artificial intelligence models. This involves tasks such as categorizing images, annotating text, and ensuring that data is accurate and relevant for machine learning algorithms. They work closely with data scientists and engineers to improve the quality of AI systems by providing clean and well-labeled datasets. The role is a great way to start a career in artificial intelligence, as it offers hands-on experience with data and insights into how AI models are developed.

What are the key skills and qualifications needed to thrive as an entry level AI data trainer?

To thrive as an Entry Level AI Data Trainer, you need strong analytical skills, attention to detail, and a foundational understanding of data annotation processes, often supported by a bachelor's degree in a related field. Familiarity with data labeling tools, content management systems, and basic programming or scripting (such as Python) is typically required. Excellent communication, teamwork, and adaptability help you effectively interpret guidelines and collaborate with cross-functional teams. These skills ensure high-quality data preparation, which is essential for developing accurate and reliable AI models.

What types of tasks and collaboration can I expect as an entry level AI data trainer?

As an Entry Level AI Data Trainer, you will primarily be responsible for labeling, annotating, and curating data sets to help improve machine learning models. Your daily tasks often include reviewing text, images, or audio and providing accurate labels according to detailed guidelines. You will frequently collaborate with data scientists, engineers, and other trainers to ensure consistency and quality in the data. This collaborative environment offers valuable exposure to the AI development process, and high performers often have opportunities to advance into more specialized roles over time.

What is the difference between Entry Level Ai Data Trainer vs Data Annotator?

AspectEntry Level Ai Data TrainerData Annotator
Required CredentialsHigh school diploma or equivalent; some roles prefer basic technical skillsHigh school diploma or equivalent; no specialized certifications typically needed
Work EnvironmentOffice or remote; collaborative with AI teamsOffice or remote; focused on labeling data
Employer & Industry UsageTech companies, AI startups, research labsTech companies, data labeling services, AI firms

While both roles involve working with data, Entry Level Ai Data Trainers focus on training AI models by providing structured data and feedback, often requiring some technical understanding. Data Annotators primarily label and categorize data to prepare datasets for AI training. The roles are similar in work environment and industry but differ in responsibilities and skill requirements.

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

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

What are popular job titles related to Entry Level Ai Data Trainer jobs in Michigan?

For Entry Level Ai Data Trainer jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Entry Level Ai Data Trainer jobs in Michigan look for?

The top searched job categories for Entry Level Ai Data Trainer jobs in Michigan are:

Entry Level Ai Data Trainer jobs near you
Infographic showing various Entry Level Ai Data Trainer job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 13% Part Time, 2% Temporary, 3% Contract, and 1% Nights. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

AI Data Engineer

IntraEdge

Detroit, MI

$113K - $136K/yr

Full-time

Re-posted 10 days ago

Job description

Job Description: 

We are seeking an experienced and highly skilled AI Data Engineer to join our team. The successful candidate will be responsible for designing, building, and maintaining the data infrastructure and pipelines that power our AI, machine learning (ML), agentic AI, and generative AI (GenAI) initiatives. This role requires strong expertise in data engineering best practices and a deep understanding of the unique data needs of AI models. 
Key responsibilities
  • Build AI-ready data pipelines: Design, construct, and optimize scalable Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) pipelines specifically for AI and ML models.
  • Architect data solutions: Develop and manage data architectures, including data lakes, data warehouses, and vector databases, to support various AI workloads.
  • Ensure data quality and governance: Implement data validation, security, and governance policies to ensure the integrity, accessibility, and compliance of data used in AI models.
  • Support AI model lifecycle: Collaborate with data scientists and ML engineers to prepare, integrate, and manage large-scale datasets for model training and deployment.
  • Manage real-time data: Develop streaming data pipelines using technologies like Apache Kafka to support real-time AI applications and analytics.
  • Optimize cloud infrastructure: Utilize AWS cloud computing platforms to build, deploy, and scale AI data solutions efficiently.
  • Deploy AI models: Automate the training and deployment of AI/ML models into production via APIs and microservices.
  • Monitor and troubleshoot: Implement data observability tools to monitor pipeline health, identify data drift, and quickly resolve any data quality issues that may impact model performance.
  • AI-assisted development: Use AI assistants like Copilot in Microsoft Fabric notebooks to generate, explain, and fix code, accelerate data analysis, and streamline data transformation tasks.
Required qualifications
  • Education: A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field is typically required.
  • Experience: Proven experience in a data engineering or similar role, with specific experience supporting AI and ML projects.
  • Programming: Fluency in programming languages such as Python and SQL, and familiarity with others like Java or Scala.
  • Frameworks: Hands-on experience with ML frameworks like TensorFlow, PyTorch, and Scikit-learn, as well as LLM-specific tools like LangChain or LlamaIndex.
  • Big data: Experience with distributed data processing frameworks such as Apache Spark and Hadoop.
  • Cloud platforms: Proficiency with at least one major cloud provider (AWS, Azure, or GCP) and its AI data-related services.
  • Databases: Expertise in both relational (SQL) and NoSQL databases, including vector databases for GenAI applications.
  • DevOps and MLOps: Experience with CI/CD, Docker, and ML lifecycle management tools like MLflow is highly valued.

Job Description: 

We are seeking an experienced and highly skilled AI Data Engineer to join our team. The successful candidate will be responsible for designing, building, and maintaining the data infrastructure and pipelines that power our AI, machine learning (ML), agentic AI, and generative AI (GenAI) initiatives. This role requires strong expertise in data engineering best practices and a deep understanding of the unique data needs of AI models. 
Key responsibilities
  • Build AI-ready data pipelines: Design, construct, and optimize scalable Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) pipelines specifically for AI and ML models.
  • Architect data solutions: Develop and manage data architectures, including data lakes, data warehouses, and vector databases, to support various AI workloads.
  • Ensure data quality and governance: Implement data validation, security, and governance policies to ensure the integrity, accessibility, and compliance of data used in AI models.
  • Support AI model lifecycle: Collaborate with data scientists and ML engineers to prepare, integrate, and manage large-scale datasets for model training and deployment.
  • Manage real-time data: Develop streaming data pipelines using technologies like Apache Kafka to support real-time AI applications and analytics.
  • Optimize cloud infrastructure: Utilize AWS cloud computing platforms to build, deploy, and scale AI data solutions efficiently.
  • Deploy AI models: Automate the training and deployment of AI/ML models into production via APIs and microservices.
  • Monitor and troubleshoot: Implement data observability tools to monitor pipeline health, identify data drift, and quickly resolve any data quality issues that may impact model performance.
  • AI-assisted development: Use AI assistants like Copilot in Microsoft Fabric notebooks to generate, explain, and fix code, accelerate data analysis, and streamline data transformation tasks.
Required qualifications
  • Education: A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field is typically required.
  • Experience: Proven experience in a data engineering or similar role, with specific experience supporting AI and ML projects.
  • Programming: Fluency in programming languages such as Python and SQL, and familiarity with others like Java or Scala.
  • Frameworks: Hands-on experience with ML frameworks like TensorFlow, PyTorch, and Scikit-learn, as well as LLM-specific tools like LangChain or LlamaIndex.
  • Big data: Experience with distributed data processing frameworks such as Apache Spark and Hadoop.
  • Cloud platforms: Proficiency with at least one major cloud provider (AWS, Azure, or GCP) and its AI data-related services.
  • Databases: Expertise in both relational (SQL) and NoSQL databases, including vector databases for GenAI applications.
  • DevOps and MLOps: Experience with CI/CD, Docker, and ML lifecycle management tools like MLflow is highly valued. 
Education:Employment Type: FULL_TIME
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About IntraEdge

Sourced by ZipRecruiter

At heart, we are a technology, products and services organization In our soul, it’s the people who make us what we are — the professionals we train and connect to next-level opportunities and the experts who create innovative solutions and value for our national and international partners. It’s true that innovative technology can provide a major boost to your business, but you also need the right talent pushing it forward. This critical combination is what we offer all of our partners: cutting edge tech solutions and the expertise to bring it to life.

Industry

It services

Company size

1,001 - 5,000 Employees

Headquarters location

Chandler, AZ, US

Year founded

2002

Social media

Instagram

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