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Ai Optimization Jobs in Michigan (NOW HIRING)

Autodesk

Senior Cloud & AI FinOps Analyst

Novi, MI · On-site

$82K - $109K/yr

As generative AI tools become deeply embedded in our engineering and corporate workflows, you will ... Identify cost optimization opportunities and productize them into repeatable, automated motions ...

Autodesk, Inc.

Senior Cloud & AI FinOps Analyst

Novi, MI · On-site

$82K - $109K/yr

As generative AI tools become deeply embedded in our engineering and corporate workflows, you will ... Identify cost optimization opportunities and productize them into repeatable, automated motions ...

Stellantis

AI Coding Product Leader

Auburn Hills, MI · On-site

... optimization. • Experience implementing AI-driven productivity improvements across development, testing, documentation, code review, and automation workflows. • Ability to define validation ...

HTC Global Services

Data & AI Architect

Grand Rapids, MI · On-site

$61.25 - $78.75/hr

Performance & Optimization * Optimize query performance and storage costs. * Design partitioning, clustering, indexing, and caching strategies. * Improve platform scalability and reliability. AI ...

company826

AI/ML and Data Engineer

Southfield, MI · On-site +1

$104K - $125K/yr

Lead the design, development, and deployment of manufacturing-focused AI solutions, including predictive maintenance, anomaly detection, process optimization, and related applied machine learning use ...

SME

AI/ML and Data Engineer

Southfield, MI · On-site

$104K - $125K/yr

Lead the design, development, and deployment of manufacturing-focused AI solutions, including predictive maintenance, anomaly detection, process optimization, and related applied machine learning use ...

K Group Companies

AI Engineer - On Site

Grand Rapids, MI · On-site

$110 - $150/hr

Working alongside the AI Enablement Team and practice leadership, this role leads the design, build, and ongoing optimization of AI-powered solutions for both internal operations and external client ...

Socket.dev

AI Engineer - On Site

Grand Rapids, MI · On-site

$90 - $130/hr

Working alongside the AI Enablement Team and practice leadership, this role leads the design, build, and ongoing optimization of AI-powered solutions for both internal operations and external client ...

Pwc

AI Engineer

Grand Rapids, MI · On-site

$50K - $112K/yr

... Optimizing open-weight language models, including LLaMA, Mistral, and Gemma, for local and cloud ... for AI projects - Utilizing machine learning libraries like Scikit-Learn for data analysis ...

VML

Managing Director, Product AI (Detroit)

Detroit, MI · On-site

$230K - $241K/yr

Utilize AI for advanced audience targeting, campaign performance optimization, programmatic media buying, and real-time campaign adjustments. * Data & Analytics: Implement AI-powered solutions for ...

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Ai Optimization information

What are common challenges faced by professionals in AI optimization roles, and how can they be overcome?

Professionals in AI Optimization often encounter challenges such as balancing model accuracy with computational efficiency, handling large and complex datasets, and staying updated with rapidly evolving algorithms. To overcome these, it's important to collaborate closely with data engineers and domain experts, utilize scalable computing resources, and continuously invest in learning new optimization techniques. Participating in knowledge-sharing forums and leveraging open-source tools can also help address these challenges effectively.

What are the key skills and qualifications needed to thrive as an AI optimization specialist, and why are they important?

To thrive as an AI Optimization Specialist, you need a strong background in computer science, mathematics, and machine learning, often supported by a degree in a related field. Proficiency with programming languages like Python, optimization frameworks (such as TensorFlow or PyTorch), and knowledge of cloud platforms are typically required, along with relevant certifications. Analytical thinking, problem-solving, and effective communication are essential soft skills for translating complex data into actionable solutions. These skills ensure the development of efficient, scalable AI models that drive business value and innovation.

What is the difference between Ai Optimization vs Data Scientist?

AspectAi OptimizationData Scientist
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of AI/ML frameworksDegree in Statistics, Computer Science, or related fields; proficiency in programming and statistical analysis
Work EnvironmentTech companies, AI-focused teams, R&D departmentsResearch institutions, tech firms, finance, healthcare
Employer & Industry UsagePrimarily in AI development, machine learning optimization projectsData analysis, predictive modeling, data-driven decision making

Ai Optimization specialists focus on enhancing AI models' performance and efficiency, often working on machine learning algorithms and deployment. Data Scientists analyze large datasets to extract insights, build predictive models, and support decision-making. While both roles require strong technical skills and knowledge of data and algorithms, Ai Optimization is more specialized in refining AI systems, whereas Data Scientists have a broader scope in data analysis and interpretation.

What is AI optimization?

AI optimization involves developing and applying algorithms to improve the performance, efficiency, or accuracy of artificial intelligence systems. AI optimization specialists often work with machine learning models, tuning parameters, and using tools like Python or TensorFlow to enhance AI capabilities. Strong analytical skills and knowledge of optimization techniques are essential for this role.

Which AI Optimization job is highly paid?

Senior AI Optimization engineers and machine learning engineers specializing in AI model efficiency and deployment tend to have the highest salaries in the field. These roles often require advanced skills in deep learning, programming, and data analysis, and they typically command higher compensation due to their technical complexity and impact on business performance.

What are popular job titles related to Ai Optimization jobs in Michigan?

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

What job categories do people searching Ai Optimization jobs in Michigan look for?

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

What cities in Michigan are hiring for Ai Optimization jobs?

Cities in Michigan with the most Ai Optimization job openings:

Ai Optimization jobs near you
Infographic showing various Ai Optimization job openings in Michigan as of August 2026, with employment types broken down into 73% Full Time, 21% Part Time, 2% Temporary, 3% Contract, and 1% Nights. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Senior Technical Fellow - Edge Optimization Architecture

Stellantis

Auburn Hills, MI • On-site

Full-time

Re-posted 9 days ago

Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 131 frontline employees who took The Breakroom Quiz

13th of 45 rated automakers

Job description

As a Senior Technical Fellow for Edge Optimization Architecture, you will define and drive the transformation from traditional distributed ECU architectures to a software-defined, centralized compute model with optimized edge nodes (Zero-Edge / Zonal Architecture).
You will shape the end-to-end architectural strategy for edge systems, ensuring optimal balance between centralized HPC compute and distributed edge functions, maximizing performance, scalability, cost efficiency, and reuse across vehicle programs.
This role requires deep expertise in E/E architecture, embedded software, networking, and system optimization, combined with strong leadership to influence enterprise-wide transformation and guide engineering teams through next-generation architecture adoption.
Key Responsibilities
1 - Architectural Leadership (Edge Optimization Strategy)
  • Define and drive the Edge Optimization Architecture vision, including:
  • Zonal architecture (I/O aggregators, domain/zonal ECUs)
  • Centralized compute (HPC / Brain platforms)
  • Function allocation across edge and central layers
  • Establish architectural principles for:
  • Minimizing edge complexity
  • Maximizing software centralization and reuse
  • Enabling scalable software-defined vehicle platforms

2- System Optimization & Functional Allocation
  • Lead system-level optimization strategies across:
  • CPU, memory, network bandwidth, and latency
  • Function placement (edge vs HPC)
  • Define and enforce function allocation rules and trade-offs:
  • Safety-critical vs centralized execution
  • Latency-sensitive vs cloud/offload capable workloads
  • Drive resource budgeting and KPI-based architecture validation

3- Innovation & Technology Leadership
  • Lead innovation in:
  • Zero-Edge / reduced ECU architectures
  • Ethernet-based vehicle networking
  • Service-Oriented Architectures (SOA) and middleware
  • AI-driven system optimization and resource prediction
  • Evaluate and guide adoption of emerging technologies:
  • HPC platforms, virtualization, containerization
  • Edge abstraction layers and adaptive middleware

4- Technical Expertise (End-to-End E/E + SW Stack)
  • Provide deep expertise in:
  • E/E system architecture (vehicle-level)
  • Embedded software architecture (AUTOSAR Classic/Adaptive, POSIX, RTOS)
  • High-speed automotive networking (CAN, LIN, Ethernet)
  • Distributed vs centralized compute models
  • Lead technical decisions on:
  • Zonal controller design
  • Sensor/actuator integration models
  • Data flow and service communication patterns

4- Cross-Domain Integration & Collaboration
  • Collaborate across domains:
  • ADAS, Body, Infotainment, Connectivity, Powertrain
  • Drive consistent architecture across:
  • Hardware, system, and software organizations
  • Ensure alignment between:
  • Functional architecture
  • Network architecture
  • Software platform strategy

5- Performance Optimization & Continuous Monitoring
  • Define and govern architecture KPIs:
  • CPU load, memory footprint, network utilization
  • Latency, determinism, and scalability metrics
  • Drive continuous monitoring and predictive optimization frameworks
  • Lead root cause analysis and resolution of system bottlenecks

6- Mentorship & Technical Leadership
  • Mentor senior architects and engineering leaders across domains
  • Build organizational capability in:
  • Edge optimization principles
  • Software-defined architecture
  • Foster a culture of:
  • Engineering excellence
  • Data-driven decision making
  • Continuous improvement

7- Governance & Operational Support
  • Actively support program execution:
  • Critical issue resolution
  • Technical trade-offs and arbitration
  • Milestone and architecture readiness reviews
  • Define and enforce:
  • Architectural guidelines
  • Design rules and best practices

8- Documentation & Standards
  • Establish and maintain:
  • Reference architectures for edge optimization
  • Design guidelines for zonal and centralized architectures
  • Standardized interfaces and abstraction layers
  • Ensure traceability:
  • System → Software → Deployment architecture

9- Stakeholder Engagement & Executive Influence
  • Engage executive leadership on:
  • Architecture strategy
  • Trade-offs and investment decisions
  • Provide clear, data-driven insights on:
  • Cost vs performance vs complexity trade-offs
  • Influence enterprise-wide transformation initiatives

10 - External Representation
  • Represent the organization in:
  • Industry consortiums (SDV, AUTOSAR, Ethernet standards)
  • Technology forums and conferences

11- Knowledge Sharing & Capability Building
  • Identify training needs and lead:
  • Architecture upskilling programs
  • Cross-domain knowledge sharing initiatives
  • Promote reuse of best practices across global teams

Qualifications
  1. Education
  • Master's degree in Computer Science, Electrical Engineering, or related field
  • PhD preferred (Systems Architecture, Distributed Systems, or Automotive E/E)

2- Experience
  • 15+ years in automotive software and system development
  • 10+ years in:
  • E/E architecture
  • Software architecture
  • System-level design and optimization
  • Proven experience in:
  • SDV transformation, HPC-based architectures, or zonal architectures

3- Technical Skills
  • Expert knowledge of:
  • Automotive software standards (AUTOSAR Classic & Adaptive)
  • Embedded systems (C/C++, RTOS, POSIX systems)
  • Strong expertise in:
  • Vehicle networks (CAN, LIN, Ethernet, TSN)
  • Distributed and centralized compute architectures
  • Middleware and service-oriented communication
  • Strong understanding of:
  • Memory management, multi-core systems, and real-time constraints
  • Virtualization and abstraction layers
  • Functional safety (ISO 26262) and system robustness

4- Leadership
  • Demonstrated ability to:
  • Lead enterprise-level architecture transformations
  • Influence senior leadership and cross-functional teams
  • Strong communication and executive presentation skills

5- Problem-Solving
  • Exceptional ability to:
  • Solve complex cross-domain system challenges
  • Navigate trade-offs under constraints (cost, safety, performance)

6- Innovation
  • Proven track record of:
  • Driving architectural innovation
  • Influencing industry direction in SDV / E/E evolution

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