1

Applied Ai Engineer Jobs in Michigan (NOW HIRING)

The Applied AI Engineer turns ideas into production-ready AI solutionsspanning feasibility, data engineering, model development, and integration. Operating within the AI Strategy team, this role ...

Applied AI Engineer

Detroit, MI

$113K - $136K/yr

The Applied AI Engineer turns ideas into production-ready AI solutions spanning feasibility, data engineering, model development, and integration. Operating within the AI Strategy team, this role ...

The Applied AI Engineer turns ideas into production-ready AI solutions spanning feasibility, data engineering, model development, and integration. Operating within the AI Strategy team, this role ...

Principal Applied AI Engineer, Finance We are seeking a Principal Applied AI Engineer to lead the design and delivery of next-generation AI and predictive models that transform financial decision ...

Define long-term architecture and engineering standards for Applied AI systems to maximize reuse, reliability, and impact across multiple product areas. * Partner with business sponsors to translate ...

Java AI Engineer

Farmington Hills, MI · On-site

$51 - $69.75/hr

We are looking for an AI Engineer / Applied AI Developer. The ideal candidate should have strong hands-on development skills, with a passion for building AI-powered proof-of-concepts and exploring ...

AI Engineer / Applied AI Developer Okemos, MI (Hybrid): Minimum of 3 days per week onsite in Okemos. or 100% Remote: Open only to Senior-level candidates located in Eastern Time (EST). Must Have ...

Sr. Applied AI Engineer (Claude/Codex)

Detroit, MI · On-site

$121K - $159K/yr

You Are As an Applied AI team member at Accenture, you will be a Pre-Sales architect focused on ... The Work Working closely with our Sales, Product, and Engineering teams, you'll guide customers ...

New

Act as a technical mentor and thought leader , setting best practices for LLM engineering and applied AI. * Stay current with advances in LLMs, agent frameworks, AI infrastructure, and applied ...

New

next page

Showing results 1-20

Applied Ai Engineer information

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

To thrive as an Applied AI Engineer, you need strong proficiency in programming (especially Python), machine learning algorithms, statistics, and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud platforms (such as AWS or Azure), and knowledge of data management tools are typically required. Excellent problem-solving, communication, and teamwork skills help you translate complex models into real-world solutions and collaborate across disciplines. These competencies ensure you can effectively develop, deploy, and maintain AI systems that drive business value.

What does an applied AI engineer do?

An applied AI engineer develops and implements artificial intelligence models and algorithms to solve real-world problems. They work with data, machine learning frameworks, and programming languages like Python or TensorFlow to create practical AI solutions for businesses or products.

What is the difference between Applied Ai Engineer vs Data Scientist?

AspectApplied Ai EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; experience with AI frameworksBachelor's or Master's in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentDevelops and deploys AI models in production environmentsAnalyzes data to extract insights and build predictive models
Industry UsageUsed in tech, healthcare, finance for deploying AI solutionsUsed across industries for data analysis and modeling

Applied Ai Engineers focus on implementing and deploying AI models in real-world applications, while Data Scientists primarily analyze data to generate insights and build predictive models. Both roles require similar educational backgrounds but differ in their core responsibilities and work environments.

What are some common challenges applied AI engineers face when deploying AI models into production environments?

Applied AI Engineers often encounter challenges such as ensuring models perform consistently on real-world data, optimizing models for speed and scalability, and integrating AI solutions with existing systems. Managing data privacy, monitoring for model drift, and maintaining robust documentation are also key concerns. Collaboration with DevOps, data engineering, and product teams is essential to address these challenges effectively and deliver reliable AI-driven solutions.

How much does an applied AI engineer make?

An applied AI engineer's salary varies based on experience, location, and industry, but typically ranges from $80,000 to $150,000 annually. Senior roles or those with specialized skills in machine learning, deep learning, and programming languages like Python or TensorFlow tend to earn higher salaries.
What are popular job titles related to Applied Ai Engineer jobs in Michigan? For Applied Ai Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Applied Ai Engineer jobs in Michigan look for? The top searched job categories for Applied Ai Engineer jobs in Michigan are:
What cities in Michigan are hiring for Applied Ai Engineer jobs? Cities in Michigan with the most Applied Ai Engineer job openings:
Infographic showing various Applied Ai Engineer job openings in Michigan as of August 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 100% In-person job distribution.

Full-time

Posted 17 days ago


Job description

Job Summary:

The Applied AI Engineer turns ideas into production-ready AI solutionsspanning feasibility, data engineering, model development, and integration. Operating within the AI Strategy team, this role accelerates Little Caesars' AI future by rapidly prototyping and piloting high-impact use cases.

This role will partner closely with Data Engineering, Architecture, Product, and Application Development teams toensurethe teamcan rapidlyprototype within a secureenvironment. The ideal candidate can work across the stack, with experience in platforms such as Databricks and the ability to move solutions from data pipelines and experimentation through APIs, user experiences, and production support.

Key Responsibilities:

  • Design, build, and deploy end-to-end AI solutions that span data ingestion, transformation, model development, evaluation, deployment, and application integration
  • Develop scalable data pipelines and feature engineering workflows using modern data platforms, including Databricks
  • Build and productionize machine learning and generative AI solutions that address prioritized business use cases
  • Create APIs, services, and application components that embed AI capabilities into internal tools, workflows, and user-facing experiences
  • Work with architecture and platform teams toestablishreusable patterns for modelserving,orchestration, monitoring, and secure deployment
  • Collaborate with product, business, and technical stakeholders to translate requirements into practical AI-enabled solutions with measurable impact
  • Support proof-of-concepts, pilots, and production implementations while balancing speed, scalability, maintainability, and responsible AI practices
  • Partner with data governance, security, and infrastructure teams to ensure AI solutions meet enterprise standards for privacy, reliability, and compliance
  • Stay current on emerging AI engineering practices, frameworks, and tools, and recommend technologies that improve delivery speed and solution quality
  • Mentor teammates and contribute to the evolution of engineering standards, reusable components, and AI platform capabilities

Required Knowledge, Skills and Abilities:

  • Bachelor's orMaster's degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical field, with experience building and deploying AI or machine learning solutions in production environments.Equivalent experiencemay be considered in lieu offormaldegree.
  • 2+ years of experience developing end-to-end AI solutions, including data pipelines, model training, evaluation, deployment, and application or API integration
  • Strong programming skills in Python and SQL, with the ability to build maintainable, production-quality code and integrate open-source AI frameworks
  • Hands-on experience with data engineering concepts such as data modeling, transformation, orchestration, and feature preparation for AI workloads
  • Experience building services, APIs, or lightweight applications that operationalize AI capabilities for end users or internal teams
  • Experience with machine learning, generative AI, and applied AI patterns such as retrieval, recommendation, forecasting, optimization, or intelligent assistants
  • Experience with secure development practices, data privacy controls, and operational monitoring for AI and data solutions

Preferred Knowledge, Skills and Abilities:

  • Knowledge of cloud and hybrid data architectures and how storage, compute, and governance choices influence AI solution design
  • Understanding of modern product and engineering practices such as Agile, DevOps, CI/CD,MLOps, and responsible AI delivery
  • Experience with Databricks, notebooks, model serving,MLflow, and related cloud services such as Azure AI Foundry, Microsoft Fabric, or Azure Data Factory

Working Conditions:

  • This position may require minimal travel to vendor locations, assessment atrestaurantsand Ilitch Companies facilities, datacentersor seminars/networking.

Competencies:

  • Demonstrated comfort in ambiguity and ability to work in a fast-paced continuous delivery environment
  • Ability to communicate technical concepts, architecture decisions, and solution tradeoffs clearly to both technical and non-technical stakeholders
  • Practiced at solving ambiguous business problems through structured thinking, iterative delivery, and cross-functional collaboration
  • Excellent written and verbal communication skills with the ability to document technical solutions and support collaborative delivery

Disclaimer:

The above is intended to describe the general content of and requirements for the performance of this job. It is not to be construed as an exhaustive statement of duties, responsibilities, or requirements.

All items listed above are illustrative and not comprehensive. They are not contractual in nature and are subject to change at the discretion of Little Caesars Enterprises Inc.


Little Caesar Enterprises, Inc. is an Equal Employment Opportunity employer. All qualified applicants will receive consideration for employment without regards to that individual's race, color, religion or creed, national origin or ancestry, sex (including pregnancy), sexual orientation, gender identity, age, physical or mental disability, veteran status, genetic information, ethnicity, citizenship, or any other characteristic protected by law.
The Company will strive to provide reasonable accommodations to permit qualified applicants who have a need for an accommodation to participate in the hiring process (e.g., accommodations for a job interview) if so requested.
This company participates in E-Verify. Click on any of the links below to view or print the full poster.
E-Verify and Right to Work.

PRIVACY POLICY