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Ai Coder Jobs in Michigan (NOW HIRING)

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Staff Software Engineer - AI II

Ann Arbor, MI · Hybrid

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Comfortable using AI coding tools (Copilot, Cursor, Cline, Claude Code) to quickly understand codebases, generate solutions, and accelerate development. * Able to work with AI agents to scale output ...

Apex Systems

AI Engineer

Dearborn, MI · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

AI Platform Engineer Location: Hybrid - 4 days/week onsite | Must be willing to interview in person ... Leverage modern agent development tools and coding assistants. Full-Stack Engineering * Develop ...

Tech Tammina LLC

Sr Full Stack Java Developer

Okemos, MI · On-site

$47.50 - $61.25/hr

Hands-on experience using AI coding assistants (e.g., GitHub Copilot) for code generation, debugging, and optimization * Ability to effectively write, refine, and iterate prompts to guide AI tools ...

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Ai Coder information

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How much do ai coder jobs pay per hour?

As of Aug 18, 2026, the average hourly pay for ai coder in Michigan is $23.96, according to ZipRecruiter salary data. Most workers in this role earn between $16.54 and $30.19 per hour, depending on experience, location, and employer.

What is an AI coder?

AI Coders are professionals who develop, implement, and maintain artificial intelligence (AI) systems and applications. They use programming languages such as Python, Java, and R to write code that enables machines to perform tasks that typically require human intelligence, such as learning, reasoning, and problem-solving. AI Coders often work with machine learning models, neural networks, and large datasets to create intelligent solutions for various industries. Their work can range from building chatbots and recommendation systems to designing complex algorithms for automation.

What types of projects do AI coders typically work on, and how does project collaboration usually happen?

AI Coders are often involved in developing machine learning models, creating data pipelines, and integrating AI solutions into existing products. Collaboration is a key part of the role, with AI Coders working closely with data scientists, software engineers, and product managers to translate business needs into technical solutions. Most teams use agile methodologies, daily stand-ups, and collaborative platforms like GitHub or Jira to coordinate tasks and track progress. This structure ensures that AI Coders receive frequent feedback and can contribute ideas throughout the development cycle.

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

To thrive as an AI Coder, you need strong programming skills (especially in Python), a solid understanding of machine learning concepts, and typically a degree in computer science or a related field. Familiarity with AI frameworks like TensorFlow or PyTorch, as well as experience with version control systems such as Git, is essential. Strong problem-solving abilities, attention to detail, and effective communication help you collaborate with teams and explain complex solutions. These skills and qualities are crucial for developing, optimizing, and maintaining reliable AI models that address real-world challenges.

What is the difference between Ai Coder vs Data Scientist?

AspectAi CoderData Scientist
Required CredentialsProgramming skills, knowledge of AI frameworks, certifications in AI/MLStatistics, programming, data analysis certifications
Work EnvironmentSoftware development teams, AI research labsData analysis teams, research environments
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, tech firms

While both roles involve working with data and algorithms, Ai Coders primarily focus on developing AI models and coding AI solutions, whereas Data Scientists analyze data to extract insights and inform business decisions. Ai Coders are more involved in software development, while Data Scientists emphasize statistical analysis and data interpretation.

How do you become an AI coder?

To become an AI coder, you typically need a strong foundation in programming languages such as Python or Java, along with knowledge of machine learning frameworks like TensorFlow or PyTorch. Earning a degree in computer science, data science, or a related field and gaining experience through projects or internships are common steps. Developing skills in algorithms, data structures, and mathematics is also essential for working effectively in AI development.

How much do AI coders make?

AI coders, also known as artificial intelligence programmers, typically earn between $80,000 and $150,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in machine learning and deep learning can earn higher salaries, especially in tech hubs or large companies.

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

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

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

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

What cities in Michigan are hiring for Ai Coder jobs?

Cities in Michigan with the most Ai Coder job openings:

Ai Coder jobs near you
Infographic showing various Ai Coder job openings in Michigan as of August 2026, with employment types broken down into 73% Full Time, 21% Part Time, 2% Temporary, 3% Contract, and 1% Nights. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $49,839 per year, or $24 per hour.

AI Training Specialist - Cheminformatics

micro1 AI

Ann Arbor, MI • Remote

$80 - $110/hr

Part-time

Posted 15 days ago

Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery 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.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.

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