1

Ai Tasker Jobs in Michigan (NOW HIRING)

AI Data Engineer

Detroit, MI

$113K - $136K/yr

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

Architect orchestration patterns for planning, task decomposition, memory, context management, and ... Agentic AI: building and integrating autonomous AI agents using LLM APIs and orchestration ...

About the job Mercor connects elite creative and technical talent with leading AI research labs ... Contract Compensation: $1,150-$1,450/task Location: Remote Role Responsibilities * Build a ...

Major responsibilities and tasks of the position: Design, develop, and deploy AI agents and LLM-powered applications for cybersecurity and incident response use cases.Build and improve agentic ...

Associate AI Engineer Location :  Hybrid, United States Employment Type : Full-Time Benefits ... Proficient in effectively prioritizing and executing tasks in fast-paced, high-pressure ...

AI Agentic Engineer It's more than a job We are seeking an Agentic AI Engineer to design and scale ... In this role, you will build intelligent agents capable of reasoning, planning, and executing tasks ...

AI Application Engineer

Grand Rapids, MI · On-site

$133K - $204K/yr

Tasks and Qualifications: What You Will do in This Role: * Design and implement scalable, production-grade AI/ML solutions based on AI use case requirements from internal customers. * Own agentic AI ...

AI Application Engineer

Grand Rapids, MI · On-site

$133K - $204K/yr

Tasks and Qualifications: What You Will do in This Role: * Design and implement scalable, production-grade AI/ML solutions based on AI use case requirements from internal customers. * Own agentic AI ...

Design multi-step tasks grounded in your real workflows. Require navigating multiple apps, files, and stakeholders to challenge frontier AI agents . * Collaborate with other aerospace and defense ...

AI Product Specialist Location :  Hybrid, United States Employment Type : Full-Time Benefits ... Excellent organization, scheduling, project management, and multi-tasking skills. Who We Are ...

Biostatistician

Ann Arbor, MI · Remote

$60 - $65/hr

No prior experience in AI is required -- your domain knowledge is what matters. Scope of Work * Author and review evaluation tasks that require deriving, reproducing, or validating statistical ...

Showing results 41-60

Ai Tasker information

What is the easiest AI Tasker job to get?

The easiest AI Tasker jobs are typically entry-level tasks such as data labeling, content moderation, or simple data entry, which often require minimal experience and can be completed remotely. These roles usually involve following clear instructions and may require basic computer skills or familiarity with AI tools. They are often available through online platforms that connect freelancers with short-term or micro-tasks.

What are the key skills and qualifications needed to thrive as an AI Tasker?

To thrive as an AI Tasker, you need a strong understanding of artificial intelligence concepts, data analysis, and problem-solving abilities, often supported by a background in computer science or a related field. Familiarity with AI platforms, automation tools, and workflow management systems is typically required, along with knowledge of APIs and task management software. Strong communication, attention to detail, and adaptability help AI Taskers excel when collaborating and managing diverse, technology-driven assignments. These capabilities are critical for ensuring accurate execution of AI-powered tasks and effective integration with business processes.

What is an AI Tasker?

An AI Tasker is responsible for training, testing, and refining artificial intelligence models by completing various tasks such as labeling data, reviewing AI-generated content, and providing feedback on model outputs. This role helps improve AI systems by ensuring accuracy and relevance in their responses. AI Taskers often work remotely and require attention to detail, critical thinking skills, and familiarity with AI tools.

What does an AI Tasker do?

As an AI Tasker, your day often involves reviewing and managing a variety of AI-assisted assignments such as data categorization, process automation, or QA testing on digital platforms. You may coordinate with team members to clarify project requirements, set priorities, and troubleshoot technical issues that arise during task execution. Regular collaboration with both AI engineers and project managers helps ensure deliverables meet quality standards and deadlines. The workload can be dynamic, requiring flexibility and proactive communication to handle shifting project demands efficiently.

What are the most commonly searched types of Ai Tasker jobs in Michigan? The most popular types of Ai Tasker jobs in Michigan are:
What are popular job titles related to Ai Tasker jobs in Michigan? For Ai Tasker jobs in Michigan, the most frequently searched job titles are:
What cities in Michigan are hiring for Ai Tasker jobs? Cities in Michigan with the most Ai Tasker job openings:
Infographic showing various Ai Tasker job openings in Michigan as of August 2026, with employment types broken down into 69% Full Time, 28% Part Time, and 3% Contract. Highlights an 76% In-person, 3% Hybrid, and 21% Remote job distribution.

$113K - $136K/yr

Full-time

Re-posted 29 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

IntraEdge logo

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