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Ai Monitoring Jobs in Michigan (NOW HIRING)

Tech Mirrors

AI Specialist

Rochester, MI · On-site

$150 - $200/hr

Monitor AI solution performance and continuously improve models, workflows, and deployment strategies. * Ensure AI solutions follow security, governance, compliance, and ethical AI best practices.

Reliable Software Resources

Lead Gen AI Engineer

Detroit, MI · On-site

$93K - $123K/yr

Strong knowledge of AI deployment, monitoring, security, and governance * Ability to produce traceable, explainable, and auditable AI outputs * Excellent communication skills * Ability to train and ...

OpTech LLC

AI Engineer

Detroit, MI · On-site

... monitoring, logging, testing, and deployment practices to ensure reliability, performance, and ... AI engineering, machine learning deployment, and production support practices is required. 4. ...

Kiongroup

Senior AI Data Engineer

Grand Rapids, MI

$121K - $151K/yr

Establish engineering practices for reliable production AI capabilities, including security, governance, evaluation, monitoring, and operational excellence. * Apply strong data engineering and ...

Kiongroup

Senior AI Data Engineer

Grand Rapids, MI · On-site

$121K - $151K/yr

Establish engineering practices for reliable production AI capabilities, including security, governance, evaluation, monitoring, and operational excellence. * Apply strong data engineering and ...

Stefanini Group

AI Engineer

Dearborn, MI · On-site

Stefanini is looking for an AI Engineer, Dearborn, MI (Onsite) For quick apply, please reach out ... monitored services. * Establish versioning, testing, and safe rollout practices (canary/shadow ...

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Ai Monitoring information

What is AI monitoring?

AI monitoring refers to the process of continuously observing and analyzing artificial intelligence systems to ensure they operate as intended. This includes tracking performance, detecting anomalies, ensuring compliance with ethical guidelines, and identifying potential biases or errors. Effective AI monitoring helps organizations maintain transparency, improve system reliability, and ensure that AI models make fair and accurate decisions. It is essential in applications where AI impacts critical business or societal outcomes.

What are some common challenges faced by professionals in AI monitoring roles, and how can they be addressed?

Professionals in AI Monitoring often encounter challenges such as managing large volumes of data, identifying and responding to atypical model behavior, and ensuring compliance with ethical and regulatory standards. Staying updated on the latest AI trends and best practices, utilizing robust monitoring tools, and collaborating closely with data scientists and engineers can help address these challenges. Regular training and open communication within cross-functional teams are also essential to maintain effective oversight and quickly mitigate potential issues.

What are the key skills and qualifications needed to thrive as an AI monitoring specialist, and why are they important?

To thrive as an AI Monitoring Specialist, you need a solid understanding of data analysis, machine learning concepts, and system monitoring, often supported by a degree in computer science or a related field. Familiarity with monitoring platforms like Datadog, Prometheus, or Splunk, as well as experience with scripting languages and AI model management tools, is typically required. Attention to detail, critical thinking, and strong communication skills help specialists identify issues quickly and collaborate with technical teams. These skills and qualities are crucial for ensuring AI systems operate reliably, securely, and efficiently in real-world applications.

What is the difference between Ai Monitoring vs Data Analyst?

AspectAi MonitoringData Analyst
Required CredentialsTypically requires knowledge of AI systems, programming, and data analysis toolsRequires statistical, analytical, and data visualization skills, often with a degree in data science or related fields
Work EnvironmentOften involves monitoring AI systems in real-time, using specialized software, in tech or AI-focused companiesAnalyzes data sets, creates reports, and provides insights, working in various industries like finance, marketing, or healthcare
Employer & Industry UsageCommon in AI development firms, tech companies, and organizations deploying AI solutionsWidely used across industries for decision-making, reporting, and strategic planning

While both roles involve working with data, Ai Monitoring focuses on overseeing AI system performance and ensuring operational accuracy, whereas Data Analysts interpret data to support business decisions. Understanding these differences helps in choosing the right career path or job search focus.

What are popular job titles related to Ai Monitoring jobs in Michigan?

For Ai Monitoring jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Ai Monitoring jobs in Michigan look for?

The top searched job categories for Ai Monitoring jobs in Michigan are:

Ai Monitoring jobs near you
Infographic showing various Ai Monitoring job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 12% Part Time, 2% Temporary, 5% Contract, and 1% Nights. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution.

AI Specialist

Tech Mirrors

Rochester, MI • On-site

$150 - $200/hr

Other

Posted 9 days ago

Job description

Job Title: AI Specialist

Job Location: Rochester, MI- Onsite

We are seeking an experienced AI Specialist to lead the design, development, and implementation of AI-driven initiatives that foster innovation and deliver measurable business value. This role focuses on establishing AI innovation programs, assessing organizational readiness, and driving cultural change while collaborating with cross-functional teams to identify, develop, and deploy AI solutions. The ideal candidate will possess a strong background in machine learning, data science, AI frameworks, and cloud technologies, along with the ability to translate business challenges into scalable AI solutions.

Key Responsibilities:
  • Lead the design, development, and launch of enterprise AI innovation initiatives and programs.
  • Assess organizational readiness, innovation maturity, and AI adoption opportunities across business functions.
  • Establish AI operating models, governance frameworks, success metrics, and best practices aligned with organizational technology standards.
  • Collaborate with business leaders, technical teams, and stakeholders to identify high-value AI use cases and business opportunities.
  • Gather, analyze, and document business and technical requirements for AI solutions.
  • Design, develop, train, validate, and deploy machine learning and AI models to improve business processes and decision-making.
  • Develop AI roadmaps and prioritize innovation initiatives based on business impact and strategic objectives.
  • Promote cross-functional collaboration, knowledge sharing, and adoption of AI technologies throughout the organization.
  • Evaluate emerging AI technologies, research, tools, and industry trends to recommend innovative solutions.
  • Monitor AI solution performance and continuously improve models, workflows, and deployment strategies.
  • Ensure AI solutions follow security, governance, compliance, and ethical AI best practices.
  • Prepare technical documentation, presentations, and executive updates on AI initiatives and outcomes.
  • Support organizational change management efforts to encourage AI adoption and innovation culture.
Required Qualifications:
  • Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field (Master's degree preferred).
  • 5+ years of experience designing, developing, and implementing AI, machine learning, or data science solutions.
  • Strong experience developing machine learning models using Python or R.
  • Hands-on experience with AI and machine learning frameworks such as TensorFlow, PyTorch, Keras, and Scikit-learn.
  • Experience with big data technologies including Apache Spark and Databricks.
  • Experience developing AI solutions using cloud platforms such as AWS (SageMaker, EC2, S3) and/or Microsoft Azure (Machine Learning Studio, Databricks).
  • Strong knowledge of SQL, NoSQL databases, and data engineering concepts.
  • Experience working with data visualization tools such as Tableau or Power BI.
  • Strong analytical, problem-solving, and communication skills.
  • Experience working in Agile software development environments.
  • Ability to collaborate effectively with technical and non-technical stakeholders.
Preferred Qualifications:
  • Experience leading AI innovation programs or enterprise AI adoption initiatives.
  • Experience developing AI governance frameworks and responsible AI practices.
  • Knowledge of Generative AI, Large Language Models (LLMs), prompt engineering, or AI automation platforms.
  • Experience with MLOps, CI/CD pipelines, and AI model lifecycle management.
  • Familiarity with change management methodologies and organizational transformation initiatives.
  • AI, Cloud, or Data Science certifications are a plus.
Technical Environment
  • Programming: Python, R
  • AI/ML Frameworks: TensorFlow, PyTorch, Keras, Scikit-learn
  • Big Data: Apache Spark, Databricks
  • Cloud Platforms: AWS (SageMaker, EC2, S3), Microsoft Azure (Machine Learning Studio, Databricks)
  • Databases: SQL, NoSQL
  • Analytics & Visualization: Tableau, Power BI
  • Development Tools: Jupyter Notebooks
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