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Ai Risk Jobs in Michigan (NOW HIRING)

Apexon

AI QE Architect and Governance Leader

Southfield, MI · On-site

$153K/yr

This role combines deep expertise in automation, AI/ML technologies, and agentic workflows with strong leadership in governance, risk, and complianceespecially for Energy/Utilities/Nuclear domains.

Kla

Software Engineering Manager-AI/ML

Ann Arbor, MI · On-site

Establish guardrails for responsible AI : data privacy, model risk, transparency, bias awareness, and auditability. * Drive continuous improvement through retrospectives, metrics, and adoption of ...

Deloitte

Financial Risk Senior Consultant

Detroit, MI

$115K/yr

Join our team and use advanced data, AI, and emerging technologies with industry insights to help ... Credit Risk, Liquidity Risk, Market Risk, Capital Management/Stress Testing * Knowledge of ...

Megan soft Inc

Senior AI/ML Engineer

Dearborn Heights, MI · On-site

$96K - $132K/yr

Role: Senior AI/ML Engineer (W2 Position) Location: Dearborn, MI (Hybrid) Duration: 12+ Months ... risk management, resilience, etc. Key Responsibilities: * Understand business requirements and ...

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Ai Risk information

What is the difference between Ai Risk vs Data Scientist?

AspectAi RiskData Scientist
Required CredentialsBackground in AI, risk management, certifications in AI safetyDegree in Computer Science, Statistics, or related fields; certifications in data analysis
Work EnvironmentRisk assessment teams, AI development projects, regulatory settingsData analysis teams, research labs, tech companies
Employer & Industry UsageTech firms, AI safety organizations, regulatory agenciesTech companies, finance, healthcare, research institutions
Common Search & Comparison IntentUnderstanding AI risk roles, career differencesData analysis careers, AI safety roles

Ai Risk professionals focus on identifying and mitigating risks associated with artificial intelligence systems, often working in safety, ethics, and regulatory contexts. Data Scientists analyze large datasets to extract insights, build models, and support decision-making across various industries. While both roles require technical skills, Ai Risk emphasizes safety and ethical considerations, whereas Data Scientists focus on data analysis and modeling.

What are the most commonly searched types of Ai Risk jobs in Michigan? The most popular types of Ai Risk jobs in Michigan are:
What are popular job titles related to Ai Risk jobs in Michigan? For Ai Risk jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Ai Risk jobs in Michigan look for? The top searched job categories for Ai Risk jobs in Michigan are:
What cities in Michigan are hiring for Ai Risk jobs? Cities in Michigan with the most Ai Risk job openings:
Ai Risk jobs near you
Program Manager - Supply Chain AI

Program Manager - Supply Chain AI

Stellantis

Auburn Hills, MI • On-site

$135K/yr

Full-time

Posted 11 days ago

Stellantis rating

7.4

Company rating: 7.4 out of 10

Based on 124 frontline employees who took The Breakroom Quiz

17th of 44 rated automakers

Job description

We are building an AI-enabled supply chain that senses, predicts, prescribes, and acts. As the Program Manager for the Supply Chain AI & Automation team, you will drive end-to-end delivery of a portfolio that spans data engineering, data science, agentic AI, RPA, and process mining initiatives.
This role owns the execution engine behind the team: planning and prioritization, stakeholder alignment, delivery governance, risk and dependency management, and transparent reporting. You will operate independently, bring structure to ambiguity, and partner closely with product, engineering, and business leaders to deliver measurable outcomes (cost, service, resilience, and productivity).
Responsibilities include but not limited to:
  • Own end-to-end project delivery for a portfolio of AI and automation initiatives (plan, scope, schedule, budget, risks, and outcomes)
  • Facilitate planning and delivery ceremonies (intake, prioritization, sprint planning, standups, demos, retrospectives)
  • Build and maintain integrated delivery plans that capture milestones, dependencies, and critical path across workstreams
  • Drive cross-functional stakeholder alignment across supply chain operations, IT, data/AI, security, and platform teams
  • Lead business requirements discovery and translate needs into clear epics/stories, acceptance criteria, and measurable outcomes in partnership with product and domain owners
  • Manage risks, issues, and decisions, proactively surface tradeoffs, and drive resolution
  • Establish and run delivery governance (status reporting, KPI/OKR tracking, executive readouts)
  • Coordinate release readiness for production deployments (communications, training, hypercare, and adoption tracking)
  • Drive adoption and value realization: stakeholder readiness, process updates, training enablement, communications, and adoption/KPI tracking post-launch
  • Coordinate model and agent lifecycle activities with data science/AI engineering and platform teams (release gating, monitoring review cadence, retraining triggers, incident response, and rollback plans)
  • Support vendor/partner coordination where applicable (SOW milestones, deliverables, and performance)
  • Continuously improve the team's operating model (templates, playbooks, cadence, and metrics)

Basic Qualifications:
  • Bachelor's degree in Business, Engineering, Computer Science, or a related field
  • 8+ years of professional experience in project/program management delivering data & analytics initiatives
  • Demonstrated ability to operate independently, bring structure to ambiguity, and drive delivery with minimal oversight
  • Experience managing cross-functional delivery across engineering, data/AI, and business stakeholders
  • Strong working knowledge of Agile delivery (Scrum/Kanban), including backlog management and sprint execution
  • Proven skills in dependency management, risk/issue management, and executive-ready status reporting
  • Strong communication and facilitation skills; ability to influence without authority

Preferred Qualifications:
  • Experience delivering AI/analytics, data platform, automation (RPA), or process transformation initiatives
  • Experience in supply chain domains (planning, logistics, manufacturing, procurement) and enterprise systems (ERP/WMS/TMS)
  • PMP, PMI-ACP, CSM/PSM, or SAFe certification
  • Experience with change management and adoption (communications, training, operational readiness)
  • Experience coordinating AI/ML model lifecycle in production (monitoring routines, retraining/revalidation, and controlled rollout/rollback)
  • Experience with portfolio reporting tools (Jira, Azure DevOps, Smartsheet, MS Project, Power BI)

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