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Contractual Ai Coding Trainer Jobs in Michigan (NOW HIRING)

Mercor

Permitting Expert - AI Trainer

Detroit, MI · Remote

$65 - $90/hr

Building Code & Permitting Specialists (ONLY Cal & FL) Type: Contract Compensation: $65-$90/hour ... Evaluate AI-generated outputs for correctness in permit requirements, zoning constraints, and code ...

Integra Partners

Medical Coding Specialist

Troy, MI · On-site +1

$65K - $65K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... with contractual and regulatory requirements. • Identify opportunities to improve coding ... training materials, and internal reference tools. • Participate in audits, quality improvement ...

Integra Partners

Medical Coding Specialist

Troy, MI · On-site

$65K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... with contractual and regulatory requirements. • Identify opportunities to improve coding ... training materials, and internal reference tools. • Participate in audits, quality improvement ...

Intermountain Health

PB Coding Coordinator

Lansing, MI · On-site

$31.01 - $48.84/hr

Provides education/training for medical providers and coders within the department. * Performs ... At Intermountain Health, we use the artificial intelligence ("AI") platform, HiredScore to improve ...

New

R1 RCM

Coding Integrity Specialist

Detroit, MI · On-site

$28.24 - $40.21/hr

Identify coding trends that require formal education by the R1 Education and Training team and work ... AI, and human expertise to strengthen the entire revenue cycle. With more than 20 years of ...

Ilitch

Applied AI Engineer

Detroit, MI · On-site

... code and integrate open-source AI frameworks * Hands-on experience with data engineering concepts ... They are not contractual in nature and are subject to change at the discretion of Little Caesars ...

Little Caesars

Applied AI Engineer

Detroit, MI

$113K - $136K/yr

... quality code and integrate open-source AI frameworksHands-on experience with data engineering ... They are not contractual in nature and are subject to change at the discretion of Little Caesars ...

Little Caesars

Applied AI Engineer

Detroit, MI · On-site

... code and integrate open-source AI frameworks * Hands-on experience with data engineering concepts ... They are not contractual in nature and are subject to change at the discretion of Little Caesars ...

Datavant

Profee Coding Consultant - PRN

Lansing, MI · On-site

$20 - $28/hr

  • Retirement

From fulfilling a single patient's request for their medical records to powering the AI revolution ... Comprehensive training led by a credentialed professional coding manager * Exceptional service ...

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All JobsContractual Ai Coding Trainer JobsContractual Ai Coding Trainer Jobs in Michigan

Contractual Ai Coding Trainer information

What is the difference between Contractual Ai Coding Trainer vs AI Developer?

AspectContractual Ai Coding TrainerAI Developer
CredentialsRelevant certifications in AI and coding, teaching experienceAdvanced degrees in computer science or AI, programming skills
Work EnvironmentTraining sessions, workshops, online platformsSoftware development teams, R&D labs, tech companies
Employer & Industry UsageEducational institutions, training firms, corporate trainingTech companies, startups, research organizations

While both roles involve AI and coding, a Contractual Ai Coding Trainer primarily focuses on teaching and training others in AI coding skills, often on a contractual basis. An AI Developer, however, is involved in designing, developing, and deploying AI solutions within organizations. The roles differ mainly in their focus—training versus development—and their typical work environments.

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Contractual Ai Coding Trainer jobs near you

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Lansing, MI • On-site

$180 - $240/hr

Other

Re-posted yesterday

Job description

Senior Software Engineer: Applied AI (Voice Agents & ML Systems) The pitch

We build and operate production AI voice agents that hold real phone conversations in a regulated healthcare setting, plus the machine learning and LLM pipelines around them. This is one seat that spans four disciplines that rarely come together: real‑time systems, LLM engineering, traditional machine learning, and serious cloud infrastructure, all in production, all with real consequences. If you are the kind of engineer who gets restless doing one thing, this role is the opposite problem.

What you’ll work across
  • Streaming, low‑latency speech‑to‑speech systems built on modern LLMs
  • Telephony and real‑time media (call control, live audio streaming)
  • Audio handling and the quirks of real human conversation (interruptions, timing, noise)
  • Concurrency on a latency‑sensitive path, where p99 matters and a stall is something a caller hears
  • Wrapping nondeterministic models in deterministic control so they behave reliably in production
  • Multi‑model pipelines, prompt design, and cost/latency budgeting
  • Evaluation harnesses, including LLM‑as‑judge and automated agent‑tests‑agent approaches
  • Agentic tooling that gives AI systems safe, structured access to infrastructure
Traditional (non‑LLM) machine learning
  • End‑to‑end ML pipelines: feature engineering, model training, and scheduled inference
  • Imbalanced, messy real‑world data; calibration and explainability for non‑technical consumers
  • Turning research notebooks into reproducible, auditable production pipelines
Cloud and infrastructure
  • Infrastructure as code across multiple environments (we run on AWS)
  • Managed compute, data, streaming, and orchestration services
  • Security engineering in a regulated setting: encryption, least‑privilege access, strict data‑handling discipline
  • Observability and telemetry‑driven debugging, tracing a production issue from a metric anomaly to root cause
Plus

Occasional full‑stack work on internal tools, and an engineering workflow that leans heavily on AI coding assistants, with human accountability for every change.

What you’ll actually do
  • Ship and debug code on a live, real‑time voice pipeline where latency and correctness are user‑facing
  • Design control systems around LLMs: guardrails, budgets, watchdogs, safe fallbacks
  • Build and operate LLM evaluation and batch‑analysis pipelines
  • Own traditional ML workflows from data to scheduled production inference
  • Trace production issues from a metric anomaly to root cause, including building the evidence when the cause is a vendor
Must‑haves
  • 7+ years building and operating production backend systems, with strong general‑purpose programming skills (we work primarily in Python)
  • Experience running distributed systems in the cloud; comfortable debugging from telemetry to root cause
  • Hands‑on production experience with LLMs or generative AI (any provider or framework), plus the judgment to know when not to use a model
  • Working fluency across the traditional machine learning lifecycle (you productionize; you do not need to publish)
  • Disciplined in a regulated environment: small, reviewable changes and careful handling of sensitive data
Nice‑to‑haves
  • Real‑time media or telephony experience
  • Front‑end / full‑stack ability
  • ML pipeline experience, vector search, or embeddings
  • Fluency with AI coding assistants (our workflows assume them, with human accountability for every change)
How we work

Smallest correct change wins. Every behavior change is validated against the live system. Evidence over opinion in debugging. Code review is rigorous. Safety and privacy gate everything.

This role is open only to US citizens and lawful permanent residents (Green Card holders). We cannot consider candidates who require visa sponsorship now or in the future, and we are unable to make exceptions of any kind.

How to apply
  • Your LinkedIn profile URL
  • A phone number where we can reach you

A resume is welcome but optional; the two items above are required.

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