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Learning Ai Jobs in Michigan (NOW HIRING)

Tror AI for everyone

Java AI Engineer

Farmington Hills, MI · On-site

$51 - $69.75/hr

Machine learning frameworks, or AI cloud services is a plus but not required. Must Have Technical Skills: * Python and Java (intermediate to advanced proficiency) * Ability to quickly build working ...

OUCU

eLearning Developer/Specialist

East Lansing, MI · Hybrid

$60K - $95K/yr

By leveraging modern design practices and emerging technologies, (including AI and learning analytics) this role ensures learning solutions are effective, scalable and efficient. The eLearning ...

Maddisoft

AI Specialist

Rochester, MI · On-site

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 ...

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Learning Ai information

What is a learning AI?

A Learning AI, or Artificial Intelligence that learns, refers to computer systems that can improve their performance over time by analyzing data and experiences. These systems use techniques such as machine learning and deep learning to adapt to new information, recognize patterns, and make predictions or decisions without being explicitly programmed for every task. Learning AI is used in many applications, including recommendation engines, language translation, and autonomous vehicles. As technology advances, Learning AI continues to play a crucial role in automating complex tasks and enhancing decision-making processes.

How do I start a career in learning ai?

To start a career in learning AI, develop a strong foundation in mathematics, programming (especially Python), and machine learning concepts. Gaining hands-on experience through projects, online courses, and certifications such as those from Coursera or edX can help build relevant skills and demonstrate your knowledge to employers.

Is learning AI a good career path?

Learning AI can be a strong career choice due to high demand for skills in machine learning, data analysis, and programming languages like Python. Careers in AI often require continuous learning, strong problem-solving skills, and familiarity with tools such as TensorFlow or PyTorch. The field offers opportunities across industries including technology, healthcare, finance, and automotive sectors.

What is the difference between Learning Ai vs Data Scientist?

AspectLearning AiData Scientist
Required CredentialsTypically a degree in Computer Science, AI, or related fields; certifications in AI/MLDegree in Computer Science, Statistics, or related fields; certifications in data analysis or ML
Work EnvironmentTech companies, AI startups, research labs focusing on AI developmentBusiness environments, analyzing data to inform decisions across industries
Employer & Industry UsagePrimarily in AI development, research, and product creationAcross finance, healthcare, marketing, and other sectors for data analysis

Learning Ai focuses on developing algorithms and models that enable machines to learn and improve autonomously, often involving deep learning and neural networks. Data Scientists analyze and interpret complex data to help organizations make informed decisions. While both roles require knowledge of machine learning, Learning Ai is more centered on creating AI systems, whereas Data Scientists focus on extracting insights from data.

How do learning AI professionals typically collaborate with subject matter experts to develop effective training solutions?

Learning AI professionals frequently work alongside subject matter experts (SMEs) to ensure that AI-driven training tools and content are accurate, relevant, and engaging. This collaboration often involves regular meetings to gather domain-specific knowledge, iterative review of training modules, and feedback sessions to fine-tune AI models for optimal learning outcomes. Clear communication and a strong partnership with SMEs are essential, as they help bridge technical AI capabilities with real-world educational needs, resulting in more impactful and user-friendly learning solutions.

What are the key skills and qualifications needed to thrive as a learning AI engineer?

To thrive as a Learning AI Engineer, you need a solid background in computer science, mathematics, and machine learning, often supported by a relevant degree or certification. Familiarity with programming languages like Python, machine learning libraries (such as TensorFlow or PyTorch), and cloud computing platforms is typically required. Strong problem-solving skills, adaptability, and effective communication set outstanding professionals apart in this field. These skills are crucial for building, deploying, and refining AI models that solve real-world problems efficiently and ethically.

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

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

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

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

What cities in Michigan are hiring for Learning Ai jobs?

Cities in Michigan with the most Learning Ai job openings:

Learning Ai jobs near you

AI Trainer - Microbiology Expert

micro1 AI

Sterling Heights, MI • Remote

$70 - $90/hr

Part-time

Posted 18 days ago

Job description

Role Title: Microbiologist


Role Type: Contractor


Location: Remote


micro1 is engaging Microbiologists to contribute their scientific expertise to a unique customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Key Responsibilities:

  1. Investigate and analyze the development, morphology, and behavior of microscopic organisms including bacteria, fungi, and algae.
  2. Contribute to the study of the relationship between microorganisms and disease, supporting projects involving medical microbiology.
  3. Assess the impact of antibiotics and other agents on microbial populations, providing insights for AI model accuracy.
  4. Document experimental findings and processes with a focus on clarity for AI training data.
  5. Collaborate with interdisciplinary teams to ensure scientific rigor and data integrity in AI development.
  6. Provide written and verbal expertise on microbiological phenomena and their relevance to real-world and computational contexts.
  7. Utilize rubrics and established evaluation criteria to assess data quality and support AI training workflows.


Required Skills and Qualifications:

  1. Bachelor’s degree or higher in Biology, Microbiology, Chemistry, or a related field.
  2. Extensive knowledge of bacterial, fungal, and algal systems.
  3. Demonstrated expertise in investigating microbial structure and physiology.
  4. Strong written and verbal communication skills for technical and interdisciplinary collaboration.
  5. Ability to document processes and findings clearly for integration into AI systems.
  6. Comfort working independently in a fully remote, digital-first environment.
  7. Attention to detail and commitment to scientific accuracy.


Preferred Qualifications:

  1. Prior experience developing or applying rubrics in scientific or educational contexts.
  2. Experience with AI, machine learning, or annotation projects related to biology or microbiology.
  3. Advanced degree (Master’s or PhD) in a relevant field.

Apply