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Remote Cae Fea Engineer Jobs in Michigan (NOW HIRING)

CAE/FEA Engineer

Detroit, MI ยท Remote

$170K - $235K/yr

Career Renew is recruiting for one of its clients a CAE/FEA Engineer - this is a fully remote role for US-based candidates. Salary range: 170-235K USD base plus benefits plus equity. Not open to visa ...

Posted today

Maya HTT is a world leading software developer and engineering solutions provider focused on CAE ... Flex Working Hours and 100% Remote Work. * Permanent Position, Competitive Base Salary, and Bonus.

Maya HTT is a world leading software developer and engineering solutions provider focused on CAE ... Flex Working Hours and 100% Remote Work. * Permanent Position, Competitive Base Salary, and Bonus.

Design Release Engineer

Auburn Hills, MI ยท On-site +1

$38 - $43.50/hr

Activities include coordinating CAD design, CAE, prototyping, and physical testing - as well as the ... Ability to effectively operate independently in a remote or hybrid office/remote workplace

Vehicle Design Specialist - AI Trainer

Detroit, MI ยท On-site +1

$1.1K - $1.4K/wk

Remote Role Responsibilities * Build a realistic digital workspace centered on the Drive folders ... Expertise in vehicle or subsystem design, CAE/CAD/simulation engineering , manufacturing/process ...

Remote Cae Fea Engineer information

What is the difference between Remote Cae Fea Engineer vs Remote Mechanical Design Engineer?

AspectRemote Cae Fea EngineerRemote Mechanical Design Engineer
Primary FocusFinite Element Analysis (FEA) and simulation of mechanical componentsDesign and development of mechanical parts and assemblies
Required SkillsCAE software (ANSYS, Abaqus), FEA expertise, engineering fundamentalsCAD software (SolidWorks, AutoCAD), mechanical design skills, prototyping
Work EnvironmentSimulation labs, engineering teams, remote collaborationDesign studios, manufacturing teams, remote or onsite
Industry UsageAutomotive, aerospace, industrial equipmentConsumer products, machinery, automotive

While both roles require engineering knowledge and often involve remote work, a Remote Cae Fea Engineer specializes in simulation and analysis of mechanical components, whereas a Remote Mechanical Design Engineer focuses on creating and refining physical designs. Understanding these differences helps in selecting the right career path or job search focus.

What are the most commonly searched types of Cae Fea Engineer jobs in Michigan? The most popular types of Cae Fea Engineer jobs in Michigan are:
What cities in Michigan are hiring for Remote Cae Fea Engineer jobs? Cities in Michigan with the most Remote Cae Fea Engineer job openings:
Infographic showing various Remote Cae Fea Engineer job openings in Michigan as of July 2026, with employment types broken down into 94% Full Time, and 6% Contract. Highlights an 100% Remote job distribution.

CAE/FEA Engineer

Career Renew

Detroit, MI โ€ข Remote

$170K - $235K/yr

Full-time

Posted 20 hours ago

Posted today


Job description

Career Renew is recruiting for one of its clients a CAE/FEA Engineer - this is a fully remote role for US-based candidates. Salary range: 170-235K USD base plus benefits plus equity. Not open to visa sponsorships/transfers.

We build Collaborative Intelligence™ — an always-human-in-the-loop AI system that augments humanity instead of replacing it. They work with the biggest OEMs and innovative automotive partners on cutting-edge tech like electric vehicles and autonomous systems.


You'll join a well-funded startup ($120M raised from top investors like Crosspoint Capital) with only 53 people, giving you massive ownership and impact. Work alongside brilliant minds including an SVP of Engineering who managed 6,000 engineers at Lockheed Martin for 27 years.


This Forward Deployed Engineer role puts you at the forefront of deploying AI in automotive manufacturing. You'll own client relationships and build custom solutions that bridge cutting-edge ML with mission-critical physical systems.

As a Forward Deployment Engineer specializing in Automotive deployment, you will act as the primary bridge between SynthBee’s ML technologies and the rigorous engineering standards of our tier-1 partners. You will advise leadership on the deployment of ML-powered systems within highly regulated environments, ensuring that innovation never compromises safety or compliance.

What you'll do

  • Technical Deployment & Advisory: Provide deep-domain expertise in mechanical and systems engineering to ensure ML models are physically grounded and technically viable.

  • Regulatory Alignment: Lead the translation of complex regulatory requirements (FDA, ISO, etc.) into technical constraints for ML development.

  • System Architecture: Oversee the lifecycle of complex systems, from requirements capture to V-Model verification and validation (V&V).

  • Cross-Functional Liaison: Act as the "translator" between software/ML teams and client-side software/hardware engineering departments (Mechanical, Thermal, Safety).

  • Root Cause Analysis: Utilize engineering fundamentals to troubleshoot system-level failures in the field, bridging the gap between digital predictions and physical outcomes.

Requirements:
5 - 15 years of experience as a systems engineer in the automotive industry (Mandatory)
Hands-on systems engineering ownership across the full lifecycle (requirements, ICDs, V&V) (Mandatory)
Has done external client-facing technical work (presented findings, managed relationships, or deployed at client sites) (Mandatory)
Previous experience as a Technical Product Manager at some point in their career (Nice-to-have)
Previous startup experience (Nice-to-have)
Bachelor's in Mechanical or similar engineering field (Mandatory)
Master's or PhD in a relevant engineering field (Nice-to-have)
Hands-on experience with FEA tools: Ansa (hard req) or Ansys, Abaqus (preferred)
Proficiency with CAD tools, especially CATIA V5/V6 or Hyperworks (Mandatory)
Familiarity with automotive standards (e.g., ISO 26262, ASPICE) (Nice-to-have)
Exposure to AI/ML deployment or configuration (API integration, cloud infrastructure, or agentic systems) — does not need to have trained models (Nice-to-have)
Willing to travel 35%-50% of the time for client deployments (Mandatory)