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Ai Test Engineer Jobs in Michigan (NOW HIRING)

Aquent

AI Software Test Engineer (SDET)

Ann Arbor, MI · On-site

$42.06 - $46.73/hr

As a Mid-Level AI Software Test Engineer, you will be a critical contributor to the development and deployment of robust AI solutions. You will own the end-to-end testing and automation efforts ...

G-TECH Services

Be Seen First

Automotive Test Engineer

Dearborn, MI · On-site

$37/hr

Automotive Test Engineer • Define efficient physical and virtual SW validation methods by ... By submitting your application, you acknowledge that recruiting technologies, including AI-assisted ...

Autodesk

Senior Machine Learning Test Engineer

Novi, MI · On-site +1

$103K - $134K/yr

... ML/AI systems * Strong programming skills in Python, with experience in test automation ... Familiarity with popular CAD environments tooling * Proficient in Automation and UAT test suite ...

FastTek

Software Development Engineer in Test

Okemos, MI

$45.25 - $58.50/hr

Software Development Engineer in Test (SDET) #1058369 Summary * We are seeking a forward-thinking ... AI & Hiring Disclosure We use AI tools to support parts of our hiring process, such as reviewing ...

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All JobsAi Test Engineer JobsAi Test Engineer Jobs in Michigan

Ai Test Engineer information

See Michigan salary details

$15

$38

$65

How much do ai test engineer jobs pay per hour?

As of Jul 26, 2026, the average hourly pay for ai test engineer in Michigan is $38.56, according to ZipRecruiter salary data. Most workers in this role earn between $29.13 and $45.67 per hour, depending on experience, location, and employer.

What is the difference between Ai Test Engineer vs Data Scientist?

AspectAi Test EngineerData Scientist
Required CredentialsBachelor's in CS, AI, or related field; knowledge of testing toolsBachelor's or higher in CS, Statistics, or related; proficiency in data analysis
Work EnvironmentSoftware testing teams, AI development projectsData analysis teams, AI research projects
Employer & Industry UsageTech companies, AI startups, software firmsTech companies, finance, healthcare, research institutions
Common Search & ComparisonOften compared for roles in AI testing and quality assuranceCompared for data analysis and AI model development roles

While both roles work within AI and tech environments, Ai Test Engineers focus on testing and validating AI systems, ensuring quality and performance. Data Scientists analyze data to develop models and insights. The roles are complementary but distinct in their core responsibilities.

What are AI Test Engineers?

AI Test Engineers are professionals who design, develop, and execute tests to evaluate the performance, accuracy, and reliability of artificial intelligence systems and machine learning models. They work closely with data scientists and software developers to ensure AI solutions function as intended, identifying bugs, biases, and potential risks in algorithms. Their responsibilities often include creating test cases, automating test processes, and analyzing results to improve AI system quality and compliance.

What are some common challenges AI Test Engineers face when validating machine learning models?

AI Test Engineers often encounter challenges such as ensuring the quality and fairness of machine learning models, identifying edge cases that the model may not handle well, and working with limited labeled data for testing. Additionally, interpreting test results can be complex due to the probabilistic nature of AI outputs, requiring close collaboration with data scientists to understand model behaviors. Effective communication and a strong foundation in both software testing and AI concepts are essential to address these challenges and ensure reliable AI solutions.

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

To thrive as an AI Test Engineer, you need a strong background in computer science, software testing methodologies, and a good understanding of machine learning concepts, often supported by a relevant degree. Familiarity with programming languages like Python, testing frameworks such as pytest, and tools like TensorFlow or PyTorch, along with certifications in software testing or AI, are typically required. Analytical thinking, attention to detail, and effective communication set top performers apart in this role. These skills and qualities are crucial for ensuring the reliability, accuracy, and ethical deployment of AI systems.
What are popular job titles related to Ai Test Engineer jobs in Michigan? For Ai Test Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Ai Test Engineer jobs in Michigan look for? The top searched job categories for Ai Test Engineer jobs in Michigan are:
What cities in Michigan are hiring for Ai Test Engineer jobs? Cities in Michigan with the most Ai Test Engineer job openings:
Ai Test Engineer jobs near you
Infographic showing various Ai Test Engineer job openings in Michigan as of July 2026, with employment types broken down into 70% Full Time, 20% Part Time, 9% Contract, and 1% Nights. Highlights an 58% Physical, 4% Hybrid, and 38% Remote job distribution, with an average salary of $80,210 per year, or $38.6 per hour.
Mid-Level AI Software Test Engineer

Mid-Level AI Software Test Engineer

Indotronix International Corporation

Ann Arbor, MI • On-site

Full-time

Posted 20 days ago

Job description

Mid-Level AI Software Test Engineer | Ann Arbor, Michigan, United States
Mid-Level AI Software Test Engineer
Position Summary
We are seeking a Mid-Level AI Software Test Engineer to lead the quality assurance, validation, and automation efforts for AI-powered applications, machine learning systems, AI agents, copilots, and generative AI solutions. This role combines traditional software quality engineering practices with emerging AI testing methodologies to ensure AI systems are accurate, reliable, secure, scalable, and production-ready.
The ideal candidate has a strong foundation in software testing and automation, along with experience or exposure to AI technologies such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, Model Context Protocol (MCP) integrations, and machine learning platforms. This role plays a critical part in establishing AI quality standards, evaluation frameworks, governance controls, and automated testing capabilities across the AI development lifecycle.
Professional Experience:
  • 3-6 years of software quality engineering, QA automation, or software testing experience.
  • 1-3 years of experience or practical exposure to AI, machine learning, or generative AI technologies preferred

Work Style:
This role is expected to operate with moderate independence, owning AI testing initiatives from planning through execution while collaborating closely with engineers, architects, product teams, and stakeholders to deliver high-quality AI solutions.
Mid-Level AI Software Test Engineer
(Also known as: AI Quality Engineer, Generative AI Test Engineer, AI Automation Engineer, AI Validation Engineer, SDET-AI)
Key Responsibilities
AI Quality Engineering
  • Develop and execute comprehensive testing strategies for AI applications, platforms, and services.
  • Validate AI-generated outputs for accuracy, consistency, relevance, reliability, and safety.
  • Design and perform functional, integration, end-to-end, regression, and performance testing for AI-powered solutions.
  • Create and maintain test cases for prompt-driven applications, AI agents, RAG systems, and workflow orchestration platforms.
  • Validate AI guardrails, business rules, permissions models, compliance requirements, and governance controls.
  • Conduct adversarial, negative, and edge-case testing to identify hallucinations, unsafe behavior, model drift, and failure scenarios.
  • Establish quality benchmarks and acceptance criteria for AI solutions.

Test Automation & Evaluation
  • Design, build, and maintain automated test frameworks for AI applications and services.
  • Develop automated evaluation pipelines to assess AI responses, workflows, and model behavior.
  • Integrate AI testing processes into CI/CD pipelines.
  • Implement automated quality scoring, benchmarking, and regression detection capabilities.
  • Create reusable test datasets, simulators, mocks, and validation frameworks to support scalable testing.

Platform & Integration Testing
  • Test AI agents, copilots, APIs, workflow engines, MCP integrations, and tool-calling capabilities.
  • Validate integrations with enterprise systems, external APIs, databases, and knowledge repositories.
  • Verify performance, reliability, scalability, resiliency, and availability of AI workloads.
  • Execute load, stress, and performance testing for AI applications and services.
  • Identify, document, and troubleshoot defects across application, infrastructure, model, and integration layers.

Collaboration & Continuous Improvement
  • Partner closely with software engineers, AI engineers, solution architects, product owners, and security teams.
  • Participate in solution design reviews and provide quality-related recommendations early in the development lifecycle.
  • Contribute to testing standards, methodologies, best practices, and AI quality frameworks.
  • Support production readiness reviews, defect triage, root cause analysis, and continuous improvement initiatives.
  • Promote responsible AI practices and help ensure alignment with organizational governance, privacy, risk, and compliance requirements.

Required Qualifications
  • Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related technical field.
  • 3-6 years of experience in software testing, quality assurance, quality engineering, or test automation.
  • Experience developing automated testing solutions using one or more of the following:
    • Python
    • Java
    • JavaScript / TypeScript
    • C#
  • Experience with API testing and automation frameworks.
  • Strong understanding of:
    • Test automation methodologies
    • Software Development Lifecycle (SDLC)
    • Agile development practices
    • CI/CD pipelines and DevOps principles
  • Experience testing distributed systems, web applications, APIs, and enterprise platforms.
  • Strong analytical, troubleshooting, and problem-solving skills.
  • Excellent verbal and written communication skills.

Preferred Qualifications
  • Experience testing:
    • Generative AI applications
    • LLM-based systems
    • AI agents and autonomous workflows
    • Retrieval-Augmented Generation (RAG) solutions
    • MCP-based integrations
  • Familiarity with leading AI platforms and models, including:
    • OpenAI
    • Azure OpenAI
    • Anthropic Claude
    • Google Gemini
  • Experience developing AI evaluation, benchmarking, and validation frameworks.
  • Experience testing cloud-native applications on:
    • Microsoft Azure
    • Amazon Web Services (AWS)
    • Google Cloud Platform (GCP)
  • Knowledge of:
    • Responsible AI principles
    • AI governance frameworks
    • AI risk management and compliance practices
    • Privacy and security considerations for AI systems

Required Skills : • Experience testing: o Generative AI applications o LLM-based systems o AI agents o RAG applications o MCP-based integrations • Familiarity with: o OpenAI o Claude o Gemini o Azure OpenAI • Experience building evaluation and benchmarking frameworks for AI solutions. • Experience testing cloud-native applications on Azure, AWS, or GCP. • Knowledge of responsible AI, AI governance, and AI risk management practices. AI initiatives are typically expected to align with enterprise governance, risk, privacy, and compliance requirements. Technical Skills
Basic Qualification :
Additional Skills :
Background Check : Yes
Drug Screen : No
Notes :
Selling points for candidate :
Project Verification Info :
Exclusive to Client :Yes
Face to face interview required :No
Candidate must be local :No
Candidate must be authorized to work without sponsorship :Yes
Interview times set :Yes
Type of project :
Master Job Title :
Branch Code :
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About Indotronix

Sourced by ZipRecruiter

In 1986, Indotronix established itself in the staffing space. 22 years later, Avani entered the scene, offering consulting and technology development. Finally, in 2016, the two joined forces to begin delivering talent across all areas, from Staffing to Consulting to unique platform development.

Industry

Recruiting and staffing services

Company size

1,001 - 5,000 Employees

Headquarters location

Rochester, NY, US

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