CAE Engineer

CAE Engineer

Mind Robotics is building Physical AI for real-world industrial deployment, starting with the factory floor. We believe the hardest problems in AI are solved when researchers and engineers are hands-on with the physical world every day - and we're looking for people who are passionate about robotics, value ownership, and are excited to tackle difficult problems. Join us if you want to move beyond digital intelligence and put intelligence into motion.

• Own structural CAE across the robot — arms, torso, base, and end effectors — from concept through production validation.
• Build and analyze FE models from component level to full-system assemblies: linear and non-linear static analysis for strength, stiffness, and deflection, including bolted joints, contact, and buckling.
• Perform dynamic analyses — modal, frequency response, transient, and shock / impact — covering structural resonances, base-induced vibration during locomotion, and collision events during manipulation.
• Use multibody dynamics (MBD) to derive structural load cases from real task duty cycles, including sustained static-hold and fault conditions, and flow them into component FEA and fatigue analysis.
• Own the arm and torso stiffness budget — predict tip deflection and torsional compliance and their impact on end-effector positioning accuracy.
• Correlate models with physical test (strain gauges, accelerometers, modal testing) and establish modeling standards, load-case libraries, and CAE best practices for the company.

• 5+ years of experience (or equivalent "hard tech" projects) performing structural FEA on complex electromechanical systems.
• Strong first-principles fundamentals in stress / strain, structural dynamics, and vibration — able to sanity-check every model with hand calculations.
• Proficiency in linear and non-linear static, dynamic, and modal simulation using tools such as Abaqus, Ansys, Opti Struct / Hyper Works, Nastran, or LS-DYNA.
• Experience with MBD tools (Adams, Simpack, or similar) and scripting (Python, MATLAB) for load derivation and workflow automation.
• Track record of correlating FE models against physical test data and driving design changes from the results.
• Hands-on problem-solving approach with the ability to iterate quickly.
• You are comfortable with ambiguity, move fast, and have an "engineering curiosity" that drives you to understand how the entire system works, not just your part.

• Experience in robotics, humanoids, EV structures, aerospace, or other mass- and stiffness-critical systems.
• Fatigue / durability tooling (FE-Safe, nCode Design Life) or transmission and strain-wave gearing analysis.
• Topology optimization, surrogate modeling, or large-scale DOE experience.
• PhD or research experience in structural mechanics or dynamics.