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Llm Engineer Jobs in Michigan (NOW HIRING)

Integrate LLM APIs (e.g., OpenAI, Azure OpenAI, Anthropic) into scalable applications * Develop prompt engineering strategies and manage prompt lifecycle for performance and reliability * Implement ...

Integrate LLM APIs (e.g., OpenAI, Azure OpenAI, Anthropic) into scalable applications * Develop prompt engineering strategies and manage prompt lifecycle for performance and reliability * Implement ...

This role is part of our Digital & IT organization and is focused on applying AI through hands-on software engineering, Python development, APIs, LLM-enabled solutions, workflow automation, and ...

Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector/hybrid search, and retrieval/evaluation telemetry. * Deliver governed datasets and feature ...

AI engineer

Dearborn, MI · On-site

$89K - $122K/yr

AI engineer Location: Dearborn, MI,48120- 2 days onsite in a week Employment Type: Full-time ... Experience with Generative AI - LLM and building frontend with React / Chainlit / Streamlit.

$111K - $146K/yr

Develop Python-based solutions and work with APIs, JSON payloads, model integrations, and LLM ... Help create reusable patterns, improve engineering practices, and mentor less experienced engineers ...

Reporting directly to the LLM Product Owner, this designer will collaborate closely with LLM engineering team to drive the continual evolution of the platform across visual design, usability ...

... LLM-enabled solutions, Agile delivery, and platform integration. This is not a pure research or ... Guide AI Engineers and Senior AI Engineers across multiple AI initiatives, helping ensure quality ...

$93K - $122K/yr

At Corning, we are looking for a Lead AI Engineer to help guide the design, development ... LLM-enabled solutions, Agile delivery, and platform integration. This is not a pure research or ...

Build evaluation harnesses (golden datasets, LLM-as-judge, regression suites) using AgentCore ... Partner with data engineers on Snowflake backed retrieval patterns (Cortex Analyst and Cortex ...

Build evaluation harnesses (golden datasets, LLM-as-judge, regression suites) using AgentCore ... Partner with data engineers on Snowflake backed retrieval patterns (Cortex Analyst and Cortex ...

Principal Engineer CoCounsel is our most advanced AI offering to date - combining generative and ... Analyze and tune LLM usage for cost efficiency: Partner with AI/ML and platform teams to right-size ...

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Llm Engineer information

See Michigan salary details

$22

$46

$66

How much do llm engineer jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for llm engineer in Michigan is $46.74, according to ZipRecruiter salary data. Most workers in this role earn between $37.69 and $54.28 per hour, depending on experience, location, and employer.

What does an LLM engineer do?

An LLM Engineer designs, develops, and optimizes applications that leverage large language models (LLMs). They fine-tune models, integrate them into products, and improve performance through prompt engineering and model customization. This role requires expertise in machine learning, natural language processing (NLP), and software development. LLM Engineers work closely with data scientists and developers to create AI-driven solutions for various applications such as chatbots, content generation, and code assistance.

How much do Llm engineers make?

Llm engineers typically earn between $100,000 and $180,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in machine learning and natural language processing can command higher salaries, often exceeding $200,000 with bonuses and stock options.

What are the key skills and qualifications needed to thrive as an LLM engineer?

To thrive as an LLM Engineer, you need strong expertise in machine learning, natural language processing, and proficiency with Python, along with a solid understanding of transformer-based models and deep learning frameworks like PyTorch or TensorFlow. Familiarity with cloud platforms, version control systems (e.g., Git), and tools such as Hugging Face Transformers is typically required, and certifications in AI or data science can be advantageous. Excellent problem-solving, collaboration, and communication skills help you work effectively with interdisciplinary teams and present complex findings clearly. These skills enable you to develop, fine-tune, and deploy large language models efficiently in real-world applications.

What are the most commonly searched types of Llm Engineer jobs in Michigan? The most popular types of Llm Engineer jobs in Michigan are:
What are popular job titles related to Llm Engineer jobs in Michigan? For Llm Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Llm Engineer jobs in Michigan look for? The top searched job categories for Llm Engineer jobs in Michigan are:
Infographic showing various Llm Engineer job openings in Michigan as of August 2026, with employment types broken down into 89% Full Time, 7% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $97,228 per year, or $46.7 per hour.

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Lansing, MI • Remote

$124K - $163K/yr

Full-time

Posted 22 days ago


Job description

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

AMC Health · Remote (US) · Full-time

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

Real-time voice AI

  • 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

LLM engineering

  • 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.

Work authorization (no exceptions)

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

Please submit both of the following:

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

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