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Ai Coding Jobs in Michigan (NOW HIRING)

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Ai Coding information

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How much do ai coding jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for ai coding in Michigan is $28.78, according to ZipRecruiter salary data. Most workers in this role earn between $21.78 and $34.76 per hour, depending on experience, location, and employer.

What is an AI coding?

An AI Coding job involves developing, training, and optimizing artificial intelligence models and algorithms. Professionals in this role typically work with machine learning, deep learning, and data processing to create AI-driven applications. They use programming languages like Python and frameworks such as TensorFlow or PyTorch to build intelligent systems. AI coders may also fine-tune models, improve efficiency, and deploy AI solutions for various industries.

What does an AI coder do?

Professionals in AI Coding typically spend their days designing, writing, and debugging code for machine learning models or AI-driven applications. They often collaborate with data scientists, product managers, and engineers to define project requirements, process data, and integrate AI solutions into existing systems. Regular tasks may include training and testing models, improving algorithm performance, and documenting code or processes. You’ll also likely participate in team meetings and code reviews to ensure alignment and maintain high-quality standards. This dynamic environment provides continuous opportunities to learn and innovate within the field of artificial intelligence.

What skills and qualifications are needed for AI coding?

To thrive in an AI Coding role, a strong background in computer science, programming languages (such as Python or Java), and machine learning fundamentals is essential. Familiarity with AI frameworks (like TensorFlow, PyTorch), cloud platforms, and relevant certifications (such as TensorFlow Developer Certificate) is highly valuable. Strong analytical thinking, creativity, and effective teamwork are important soft skills for excelling in this position. These skills ensure you can develop robust AI solutions, adapt to evolving technologies, and collaborate effectively with cross-functional teams.

How do I become an AI coder?

To become an AI coder, you should develop strong programming skills in languages like Python, learn machine learning frameworks such as TensorFlow or PyTorch, and gain knowledge of algorithms and data structures. Pursuing relevant education, such as a degree in computer science or related fields, and working on AI projects or internships can also help build practical experience.

What are the most commonly searched types of Ai Coding jobs in Michigan?

The most popular types of Ai Coding jobs in Michigan are:

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

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

What cities in Michigan are hiring for Ai Coding jobs?

Cities in Michigan with the most Ai Coding job openings:

Infographic showing various Ai Coding job openings in Michigan as of August 2026, with employment types broken down into 74% Full Time, 20% Part Time, 5% Contract, and 1% Nights. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $59,864 per year, or $28.8 per hour.

AI Agent Trajectory Annotator and Reviewer

Bespoke Labs

Grand Rapids, MI • On-site

$20 - $30/hr

Full-time

Posted 7 days ago


Job description

Type: Contract, hourly

Location: Remote

Hours: 20–30 per week

Pay: $20–30/hour, based on experience and language coverage

Start: Immediate

ABOUT THE ROLE

We evaluate how well advanced AI coding agents solve real engineering problems. An agent is given a real open source codebase inside a container and a hard task, then works on its own for 80 to 250 steps. A trajectory is the full record of that run — every command, result, and decision.

You will do two jobs, and you should expect either on any given day.

•Annotate — Read a trajectory nobody has looked at yet and judge it step by step.

• Review — Take an existing annotation, written by our AI tooling or another person, and confirm, correct, or reject it.

TASKS YOU'LL SEE

• Feature build — Add a working feature to a live library without breaking anything that already worked.

• Rebuild — Work out what a compiled tool does by running it, then rebuild it to match its output, exit codes, and file effects.

• Bug hunt — Find and fix twenty undocumented bugs across a dozen files with no test suite, then record what caused them.

Mostly Python and Go, with some Rust, C, and Ct+. A trajectory runs about 100 steps.

WHAT YOU JUDGE IN A TRAJECTORY

• Was the command right for the state the environment was actually in?

• Did the agent read the previous output correctly?

• Was the step wrong, or only inefficient — these are scored differently.

• Where did the run first go off course — usually earlier than where it visibly broke.

• Did the agent notice its own mistake and recover, or keep building on a false assumption?

• Did it game the grader instead of solving the task (e.g., weakening a test or hardcoding an expected value)?

WHAT WE NEED FROM YOU

• Experience — 2+ years in software engineering, DevOps, or site reliability, with real debugging in real codebases.

• Languages — Strong in Python or Go, and able to read a language you've never used.

• Linux — Comfortable with logs, running processes, build failures, and containers.

• Workflow — Everyday Git, diffs, pull requests, and issue tracking.

• Debugging — Able to work with no test suite and no error message pointing at the cause.

• Focus — Able to hold context across a long run, because step 74 can depend on step 12.

• Writing — Clear English, since every judgement needs an explanation another engineer can check.