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Ai Coder Jobs in Warren, MI (NOW HIRING)

Maxcare

AI Engineer

Birmingham, MI · On-site

$150 - $250/hr

Max AI - Stripe for Healthcare Max AI is the World's first human-free, fully-autonomous medical ... Medical doctors who code are rare. We have the best one in the world. His previous apps have driven ...

Stellantis

AI & Automation Engineer

Auburn Hills, MI · On-site

Ensure scalable, maintainable, and well-documented code following software development best ... Basic familiarity with AI-enabled tools, generative AI concepts, or AI-assisted software ...

FastTek

Commodity Senior Engineer

Dearborn, MI

$112K - $148K/yr

Use AI coding assistants and generative AI tools to accelerate software development, refactoring, debugging, documentation, and code reviews. * Cloud-Native Engineering: Architect and implement ...

Epitec

AI Engineer

Detroit, MI · On-site

$50/hr

... as-code practices, and secure software development standards. 9. Document architecture, technical designs, implementation details, and operational procedures. 10. Participate in code reviews ...

New

OneStream

AI Engineer

Birmingham, MI · On-site

Must be a self-starter, continuously be learning both best code practices and the latest technologies in the AI ecosystem. Required Education and Experience * Bachelors Degree or similar work ...

OneStream Software

AI Engineer

Birmingham, MI · On-site

Must be a self-starter, continuously be learning both best code practices and the latest technologies in the AI ecosystem. Required Education and Experience * Bachelors Degree or similar work ...

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Ai Coder information

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How much do ai coder jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for ai coder in Warren, MI is $25.82, according to ZipRecruiter salary data. Most workers in this role earn between $17.84 and $32.50 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 job categories do people searching Ai Coder jobs in Warren, MI look for?

The top searched job categories for Ai Coder jobs in Warren, MI are:

What cities near Warren, MI are hiring for Ai Coder jobs?

Cities near Warren, MI with the most Ai Coder job openings:

Ai Coder jobs near you
Infographic showing various Ai Coder job openings in Warren, MI as of August 2026, with employment types broken down into 78% Full Time, 19% Part Time, and 3% Contract. Highlights an 63% Physical, 5% Hybrid, and 32% Remote job distribution, with an average salary of $53,707 per year, or $25.8 per hour.

AI Agent Trajectory Annotator and Reviewer

Bespoke Labs

Rochester Hills, MI

$20 - $30/hr

Full-time

Posted 4 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.

Apply