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Llm Developer Jobs in Michigan (NOW HIRING)

Integrate LLM and AI capabilities into product features using the Anthropic API (Claude) and other model providers; apply prompt engineering, retrieval-augmented generation (RAG), and agentic ...

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 ...

AI Software Engineer

Ann Arbor, MI · On-site

$111K - $188K/yr

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 ...

New

AI Software Engineer

Ann Arbor, MI · On-site

$111K - $188K/yr

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 ...

New

AI Software Engineer

Ann Arbor, MI · On-site

$111K - $188K/yr

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 ...

New

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 ...

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 ...

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 ...

AI engineer

Dearborn, MI · On-site

$89K - $122K/yr

... LLM tasks, focusing on Mach1ML adoption and AI/ML democratization. Skills Required: • Work ... DevOps etc. • Experience in creating an API service with Fast API / Flask. • Experience ...

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Llm Developer information

See Michigan salary details

$22

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How much do llm developer jobs pay per hour?

As of Jul 19, 2026, the average hourly pay for llm developer in Michigan is $43.72, according to ZipRecruiter salary data. Most workers in this role earn between $34.38 and $53.03 per hour, depending on experience, location, and employer.

What is the salary of LLM developer?

The salary of an LLM developer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and the complexity of projects. Skilled developers with expertise in machine learning, natural language processing, and relevant tools like Python and TensorFlow tend to earn higher salaries.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles such as senior AI researchers or machine learning executives, often involving advanced skills in deep learning, large language models, and extensive experience. These positions may include leadership responsibilities, require specialized certifications, and offer compensation packages that include salary, bonuses, and stock options. Such roles are usually found in top tech companies or AI-focused organizations and demand a strong track record of innovation and technical expertise.

What does an LLM Developer do?

An LLM Developer designs, fine-tunes, and implements large language models (LLMs) for various applications, such as chatbots, content generation, and AI-driven tools. They work with machine learning frameworks, optimize model performance, and ensure efficient deployment. This role requires expertise in natural language processing (NLP), deep learning, and programming languages like Python.

What are the key skills and qualifications needed to thrive in the Llm Developer position, and why are they important?

To excel as an LLM Developer, you need strong expertise in natural language processing (NLP), deep learning frameworks, and programming languages such as Python, typically supported by a degree in computer science or a related field. Familiarity with machine learning libraries (like TensorFlow or PyTorch), cloud computing platforms, and experience with prompt engineering or fine-tuning large language models is crucial. Excellent problem-solving abilities, collaboration, and effective communication skills help you design solutions and work efficiently within multidisciplinary teams. These qualifications are essential for successfully building, deploying, and optimizing large language models that drive impactful AI applications.

What engineers make $500,000?

Senior machine learning engineers, including those developing large language models (LLMs), can earn $500,000 or more annually, especially with extensive experience, advanced skills in deep learning, and work at top tech companies. High compensation often includes base salary, bonuses, and stock options, particularly in competitive markets or leadership roles.

What are the typical daily tasks and responsibilities of an LLM Developer?

As an LLM Developer, your daily responsibilities often include designing, fine-tuning, and evaluating large language models to meet specific application needs. You may work on tasks such as data preprocessing, model training, performance benchmarking, and error analysis, frequently collaborating with data scientists, research engineers, and product managers. Keeping up to date with the latest advancements in NLP and integrating new techniques into production models is also a key part of the role. These tasks are usually performed in a team-oriented environment where clear communication and iterative experimentation are highly valued.

What are LLM developers?

LLM developers are software engineers who design, build, and optimize large language models used in artificial intelligence applications. They typically work with machine learning frameworks, programming languages like Python, and tools such as TensorFlow or PyTorch to develop models for tasks like natural language processing and understanding.
What are the most commonly searched types of Llm Developer jobs in Michigan? The most popular types of Llm Developer jobs in Michigan are:
What cities in Michigan are hiring for Llm Developer jobs? Cities in Michigan with the most Llm Developer job openings:
Infographic showing various Llm Developer job openings in Michigan as of July 2026, with employment types broken down into 84% Full Time, 5% Part Time, 1% Temporary, and 10% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $90,946 per year, or $43.7 per hour.

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Lansing, MI • Remote

$124K - $163K/yr

Full-time

Posted 5 days ago

New


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.