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Language Model Jobs in Michigan (NOW HIRING)

Optimal Inc.

Agentic AI Engineer

Warren, MI · On-site

This role centers on designing, building, and optimizing intelligent agent architectures powered by large language models (LLMs) and advanced reasoning frameworks. The ideal candidate brings a strong ...

Optimal Inc.

Agentic AI Engineer

Warren, MI · On-site

This role centers on designing, building, and optimizing intelligent agent architectures powered by large language models (LLMs) and advanced reasoning frameworks. The ideal candidate brings a strong ...

BDO USA

Software Engineer I, AI

Grand Rapids, MI · On-site

Implement AI features, including large language model integrations, prompts, and retrieval workflows under guidance * Proactively monitors and supports existing applications and automations

BDO

Software Engineer I, AI

Grand Rapids, MI

Implement AI features, including large language model integrations, prompts, and retrieval workflows under guidance * Proactively monitors and supports existing applications and automations

Deloitte

Customer Deployment Specialist

Detroit, MI

Experience with artificial intelligence/large language model platform features, including Skills, Model Context Protocol (MCP), Plugins, or partner-led delivery models involving systems integrators ...

FastTek

Machine Learning Engineer

Dearborn, MI

$105K - $126K/yr

Employees in this job function are responsible for designing, building, deploying, and scaling complex self-running ML solutions -- including Generative AI and Large Language Model (LLM) systems ...

Judge Group, Inc.

Midlevel AI Developer

Ann Arbor, MI · On-site

$50 - $55/hr

Build and integrate Generative AI solutions using Large Language Models (LLMs). Develop AI agents, workflows, prompts, tools, and orchestration frameworks. Implement retrieval-augmented generation ...

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All JobsLanguage Model JobsLanguage Model Jobs in Michigan

Language Model information

What are language models?

Language models are artificial intelligence systems designed to understand, generate, and manipulate human language. They are trained on vast amounts of text data to predict the next word in a sequence, answer questions, write content, translate languages, and perform other language-related tasks. Modern language models, such as those based on deep learning, have revolutionized natural language processing by enabling more accurate and context-aware interactions between humans and machines.

What is the difference between Language Model vs Data Scientist?

AspectLanguage ModelData Scientist
Required CredentialsNone specific; knowledge of NLP and AI concepts helpfulBachelor's or higher in Data Science, Statistics, or related fields
Work EnvironmentAI development teams, research labs, tech companiesBusiness, finance, healthcare, and various industries
Employer & Industry UsageUsed in AI applications, chatbots, content generationAnalyzing data, building models, providing insights

While both roles involve working with data and AI, a Language Model is an AI system designed to understand and generate human language, often developed by AI engineers. A Data Scientist analyzes data to extract insights and build predictive models, often utilizing language models as tools. Understanding the differences helps clarify career paths and job expectations in the AI and data fields.

What are the key skills and qualifications needed to thrive as a Language Model, and why are they important?

To thrive as a Language Model Engineer, you need a strong background in computer science, machine learning, and natural language processing, often supported by a relevant degree. Experience with frameworks like TensorFlow or PyTorch, and familiarity with large-scale data processing tools, are typically required. Strong analytical thinking, collaboration, and problem-solving skills help in designing effective models and working with cross-functional teams. These capabilities are crucial for developing performant and accurate language models that meet complex real-world communication needs.

What are the common challenges faced by professionals working on language model development teams?

Professionals developing language models often encounter challenges such as managing large datasets, addressing biases in training data, and optimizing model performance while balancing computational resources. Collaboration with cross-functional teams—including data scientists, engineers, and domain experts—is essential to ensure the model's accuracy and relevance. Additionally, staying current with rapid advancements in AI research and maintaining responsible AI practices are crucial aspects of the role.
What are popular job titles related to Language Model jobs in Michigan? For Language Model jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Language Model jobs in Michigan look for? The top searched job categories for Language Model jobs in Michigan are:
What cities in Michigan are hiring for Language Model jobs? Cities in Michigan with the most Language Model job openings:
Language Model jobs near you
Infographic showing various Language Model job openings in Michigan as of June 2026, with employment types broken down into 70% Full Time, 16% Part Time, and 14% Contract. Highlights an 86% In-person, and 14% Remote job distribution.
Agentic AI Engineer

Agentic AI Engineer

Optimal Inc.

Warren, MI • On-site

Full-time

Posted 23 days ago

Job description

Job Title: Agentic AI Engineer

We are seeking a highly skilled Agentic AI Engineer to support advanced R&D initiatives focused on next-generation AI agents and conversational intelligence systems. This role centers on designing, building, and optimizing intelligent agent architectures powered by large language models (LLMs) and advanced reasoning frameworks.

The ideal candidate brings a strong blend of machine learning expertise, systems thinking, and hands-on experience with agent-based architectures, and thrives in a fast-paced, research-driven environment.

Key Responsibilities

  • Design and develop agentic AI systems using GPT-style and other large language model architectures
  • Architect and optimize agent memory systems, including short-term, long-term, and retrieval-based memory
  • Implement multi-step reasoning, planning, and chain-of-thought pipelines for complex problem solving
  • Build scalable context management frameworks to support dynamic, multi-turn conversations
  • Develop text-to-structured-data pipelines for automated knowledge extraction and workflow automation
  • Collaborate with cross-functional R&D teams to integrate agent-based solutions into innovative products and research initiatives
  • Evaluate model performance and continuously improve accuracy, efficiency, and reasoning capabilities
  • Document system designs, experiments, and technical findings

Required Qualifications

  • 3-5 years of industry experience in AI/ML, LLM development, or agent-based systems
  • Strong hands-on experience with large language models (prompt engineering, fine-tuning, evaluation)
  • Experience building or working with agent frameworks, memory systems, or planning/reasoning architectures
  • Solid understanding of context handling, retrieval-augmented generation (RAG), and optimization techniques
  • Proficiency in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow)
  • Experience with tools and ecosystems such as vector databases, APIs, and distributed systems is a plus
  • Strong problem-solving skills and ability to work in research-oriented, collaborative environments

Required Education

  • Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field
  • Experience contributing to research publications, open-source projects, or experimental AI platforms