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Ai Engineer Developer Jobs in Michigan (NOW HIRING)

Socket.dev

Senior AI Engineer

Farmington Hills, MI · On-site

$140 - $210/hr

  • Medical

  • Dental

  • Retirement

Overview The Senior AI Engineer will design, develop, and deploy artificial intelligence and machine learning solutions that support Panasonic Automotive's digital transformation, engineering ...

Deloitte

AI Engineer Consultant

Detroit, MI · Hybrid

We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that ... DevOps/DevSecOps experience (CI/CD, IaC such as Terraform/CloudFormation, Docker/Kubernetes ...

Ilitch

Applied AI Engineer

Detroit, MI · On-site

... 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 ...

Little Caesars

Applied AI Engineer

Detroit, MI · On-site

... 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 ...

OneStream

Lead AI Engineer

Birmingham, MI · On-site

$97K - $128K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Lead AI Engineer Location :Hybrid, United States Employment Type :Full-Time Benefits Offered :Vision, Medical, Life, Dental, 401K Gross Annual Base Salary :USD 151,000 - 196,000 Additional variable ...

OneStream

Lead AI Engineer

Birmingham, MI

$97K - $128K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Lead AI Engineer Location :  Hybrid, United States Employment Type : Full-Time Benefits Offered : Vision, Medical, Life, Dental, 401K Gross Annual Base Salary : USD 151,000 - 196,000 ...

Little Caesars

Applied AI Engineer

Detroit, MI · On-site

$113K - $136K/yr

... DevOps, CI/CD, MLOps, and responsible AI deliveryExperience with Databricks, notebooks, model serving, MLflow, and related cloud services such as Azure AI Foundry, Microsoft Fabric, or Azure Data ...

Ford Motor Company

AI Engineer

Dearborn, MI · Hybrid

$99K - $192K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

As the AI Engineer, you should have a strong technical background and demonstrated experience in Data Science , MLOps and AI/ML Engineering. You will be responsible for the delivery of analytical ...

Judge Group, Inc.

Midlevel AI Developer

Ann Arbor, MI · On-site

$50 - $55/hr

As an AI Engineer, you will design, develop, and deploy AI-powered applications and services that drive innovation and efficiency. You will work closely with cross-functional teams-including software ...

OneStream

Senior AI Engineer

Birmingham, MI · On-site

$99K - $136K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Senior AI Engineer Location :Hybrid, United States Employment Type :Full-Time Benefits Offered :Vision, Medical, Life, Dental, 401K Gross Annual Base Salary :USD 131,000 - 170,000 Additional variable ...

OneStream

Senior AI Engineer

Birmingham, MI · On-site

$99K - $136K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Senior AI Engineer Location :  Hybrid, United States Employment Type : Full-Time Benefits Offered : Vision, Medical, Life, Dental, 401K Gross Annual Base Salary : USD 131,000 - 170,000 ...

Stellantis

AI Engineer - Supply Chain

Auburn Hills, MI · On-site

As an AI Engineer - Supply Chain, you will design and build production-grade AI agents that execute multi-step workflows, make context-aware decisions, and integrate with enterprise systems through ...

Teradata Corporation (SE)

Senior AI Engineer

Lansing, MI · On-site

$120 - $150/hr

... enhance developer productivity across the organization. You will work on AI agents and platforms across Software Development Lifecycle and design them to be scalable, reusable, and ...

New

Stellantis

Principal AI Engineer

Auburn Hills, MI · On-site

We are seeking a Principal AI Engineer with deep, hands-on experience in Large Language Models (LLMs) to lead the design, development, and deployment of enterprise-grade AI-powered automation systems ...

Barton Malow

Sr. AI Engineer

Southfield, MI · On-site

$95K - $131K/yr

Our APEX team owns the AI and engineering platform that the rest of the company builds on, and we are investing seriously in it. About the role We are hiring a Senior AI Engineer to build the systems ...

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Showing results 21-40

All JobsAi Engineer Developer JobsAi Engineer Developer Jobs in Michigan

Ai Engineer Developer information

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

AspectAi Engineer DeveloperData Scientist
Required CredentialsBachelor's in CS, AI, or related; programming skills; knowledge of ML frameworksBachelor's or higher in CS, Statistics, or related; strong analytical and statistical skills
Work EnvironmentDevelops AI models, algorithms, and systems; often in tech or R&D teamsAnalyzes data, builds models, and interprets insights; in analytics or research teams
Employer & Industry UsageTech companies, AI startups, R&D divisionsFinance, healthcare, marketing, and tech sectors

While both roles involve working with data and machine learning, Ai Engineer Developers focus on building and deploying AI systems and algorithms, whereas Data Scientists analyze data to extract insights and inform decision-making. The roles often overlap but differ in primary responsibilities and skill emphasis.

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For Ai Engineer Developer jobs in Michigan, the most frequently searched job titles are:

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The top searched job categories for Ai Engineer Developer jobs in Michigan are:

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Ai Engineer Developer jobs near you

Principle AI Engineer

Harman International Industries

Novi, MI • On-site

Full-time

Re-posted 7 days ago

Job description

A Career at HARMAN
As a technology leader that is rapidly on the move, HARMAN is filled with people who are focused on making life better. Innovation, inclusivity and teamwork are a part of our DNA. When you add that to the challenges we take on and solve together, you'll discover that at HARMAN you can grow, make a difference and be proud of the work you do every day.
About the Role
As the Principal AI Engineer, you will act as the technical leader for AI solution design, implementation, and operationalization across Harman's BI, AI, and Data ecosystem. Your primary focus will be defining how AI is applied at scale-ensuring solutions are robust, secure, explainable, testable, and production-ready.
You will lead the development of both prebuilt AI integrations and custom AI/ML solutions, while establishing enterprise standards for MLOps, model governance, and lifecycle management. You will ensure AI solutions are not isolated experiments, but fully integrated, scalable systems built on top of the data platform (Databricks).
What You Will Do
1. AI Strategy & Technical Leadership
  • AI Engineering Leadership:
  • Define best practices for AI solution design, deployment, and lifecycle management.
  • Use Case Prioritization:
  • Identify high-value AI opportunities and guide their technical execution.
  • Standards & Governance:
  • Establish standards for model development, validation, deployment, and monitoring.

2. AI Solution Architecture & Development
  • Define architectural patterns for:
  • Batch vs real-time inference
  • Feature engineering pipelines
  • Model reuse across use cases
  • Standardize implementation of common AI solutions:
  • Forecasting frameworks
  • Classification pipelines
  • Anomaly detection frameworks
  • NLP/document intelligence pipelines
  • Ensure solutions are modular, reusable, and scalable

3. Data & Platform Integration
  • Data Pipeline Alignment:
  • Ensure AI solutions effectively leverage enterprise data pipelines (e.g., Databricks).
  • Feature & Data Strategy:
  • Guide design of features and data structures required for high-performing models.
  • Platform Collaboration:
  • Work closely with Platform Engineers on infrastructure, compute, and scalability.

4. MLOps, CI/CD & Lifecycle Management
  • Define and enforce MLOps standards using MLflow, including:
  • Experiment tracking
  • Model versioning and registry
  • Promotion workflows (Dev → QA → Prod)
  • Co-design CI/CD pipelines with Platform Engineering:
  • Automated model testing
  • Validation gates before deployment
  • Environment consistency across stages
  • Establish deployment patterns:
  • Batch scoring pipelines
  • Scheduled retraining jobs
  • Model serving endpoints where needed

5. Testing, Validation & Trust
  • Define testing frameworks covering:
  • Model performance validation
  • Data validation and schema enforcement
  • Backtesting (especially for forecasting)
  • Establish standards for:
  • Drift detection (data + model)
  • Monitoring and alerting
  • Drive adoption of:
  • Explainability techniques (SHAP, feature importance)
  • Business-level validation (not just statistical metrics)

6. Security, Governance & Responsible AI
  • Define model governance standards:
  • Model approval workflows
  • Version control and rollback strategies
  • Auditability via MLflow and logging
  • Ensure:
  • Data access controls and compliance
  • Traceability from raw data → features → models → outputs
  • Drive responsible AI practices:
  • Bias detection and mitigation
  • Transparency and explainability where required

7. Cross-Functional Leadership & Mentorship
  • Technical Mentorship:
  • Guide AI Engineers and support broader team development.
  • Collaboration:
  • Align AI initiatives with Data Engineering, BI, and Platform strategies.
  • Stakeholder Engagement:
  • Translate complex AI solutions into business value and ensure adoption.

8. Innovation & Continuous Improvement
  • Technology Evaluation:
  • Continuously assess emerging AI tools, frameworks, and capabilities.
  • AI Platform Evolution:
  • Drive improvements in AI tooling, workflows, and scalability.
  • Automation & Efficiency:
  • Promote automation and reusable AI components.

What Success Looks Like
  • AI solutions are scalable, production-ready, and reusable across use cases
  • Models are governed, traceable, and continuously monitored
  • MLOps processes (MLflow, CI/CD) are standardized and widely adopted
  • AI solutions are deeply integrated into data pipelines and business workflows
  • The organization consistently delivers reliable, trusted AI at scale-not experiments

What You Need to Be Successful
  • Expert-level Python and deep experience with ML/AI frameworks
  • Strong hands-on experience with MLflow (tracking, registry, lifecycle management)
  • Deep experience building and deploying production-grade AI/ML systems on Databricks
  • Strong experience with MLOps, CI/CD pipelines, and model lifecycle governance
  • Experience standardizing AI patterns (forecasting, NLP, anomaly detection, classification)
  • Strong understanding of data pipelines and feature engineering dependencies
  • Experience with model monitoring, drift detection, and explainability techniques (e.g., SHAP)
  • Strong understanding of AI security, governance, and auditability requirements
  • Proven ability to define standards and lead technical direction across teams
  • 7+ years of experience in software engineering, data engineering, AI/ML engineering, or related technical fields
  • 3+ years designing and deploying production AI/ML systems at enterprise scale
  • Experience leading technical strategy and architecture across multiple teams or business domains
  • Experience designing and deploying Generative AI solutions using LLMs
  • Experience with Retrieval-Augmented Generation (RAG), vector search, embeddings, and prompt engineering

Bonus Points if You Have
  • Experience implementing Generative AI solutions using OpenAI, Anthropic, Gemini, or similar foundation models
  • Experience building enterprise RAG architectures, vector databases, semantic search, and agent-based AI solutions
  • Experience with Databricks Mosaic AI, Vector Search, Model Serving, Unity Catalog, and Lakehouse AI capabilities
  • Experience with cloud AI services on Azure, AWS, or Google Cloud Platform
  • Experience deploying and operating AI workloads using Kubernetes and containerized architectures
  • Experience with feature stores, online/offline feature serving, and real-time inference systems
  • Experience implementing Responsible AI frameworks, model risk management, and regulatory compliance requirements
  • Experience with experimentation platforms, A/B testing, and causal inference methodologies
  • Familiarity with modern deep learning frameworks including PyTorch, TensorFlow, and Hugging Face ecosystems
  • Experience supporting forecasting, optimization, recommendation systems, supply chain analytics, or manufacturing AI use cases
  • Experience contributing to AI platform strategy and enterprise-wide AI transformation initiatives
  • Advanced degree (MS or PhD) in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Mathematics, or a related field

Salary Ranges:
$ 125,250 - $ 183,700
HARMAN is proud to be an Equal Opportunity / Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

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