Internship, CAE Mechanical Design Engineer, Optimus (Fall 2026)

This position is expected to start August or September 2026 and continue through summer term (ending approximately December 2026) or continuing into Winter/Spring 2027 if available and there is an opportunity to do so. We ask for a minimum of 12 weeks, full-time (40 hours/week) and on-site, for most internships. Our internship program is for students who are actively enrolled in an academic program. Recent graduates seeking employment after graduation and not returning to school should apply for full-time positions, not internships. International Students: If your work authorization is through CPT, please consult your school on your ability to work 40 hours per week before applying. You must be able to work 40 hours per week on-site. Many students will be limited to part-time during the academic year. The Internship Recruiting Team is driven by the passion to recognize and develop emerging talent. Our year-round program places the best students in positions where they will grow technically, professionally, and personally through their experience working closely with their Manager, Mentor, and team. We are dedicated to providing an experience that allows the intern to experience life at Tesla by including them in projects that are critical to their team’s success. About the Team: As a CAE Engineering intern, you will guide the design of sensors and structural components using high-fidelity FE models grounded in sound engineering principles Working closely with mechanical, electrical, controls, software, and manufacturing teams, you’ll analyze and optimize designs, challenge traditional CAE methods, and pioneer more efficient, accurate approaches. This role places you at the forefront of critical design and engineering decisions, shaping a robust and reliable humanoid robot that has never been executed before.

Responsibilities

Develop and analyze comprehensive Finite Element (FE) models for Optimus, from individual components to the full system Conduct static, dynamic, structural and MBD simulations to evaluate and validate the performance against key requirements for strength, stiffness, durability and sensing Build and refine simulation workflows to assess performance across diverse operating scenarios, automate processes, documentation, and tools to improve efficiency, accuracy, and repeatability Provide design guidance to world-class engineering teams, enabling data-driven product decisions Collaborate with Test Engineering to design and validate experiments, correlate test data with simulations, and enhance predictive modeling capabilities Establish and maintain modeling standards, methods, and best practices for current and future programs Material characterization and advanced modeling of structural and sensing components Plan and execute large-scale DOEs, creating ML driven surrogate models to extract insights to drive key design decisions

Requirements

Currently pursuing a degree in Mechanical Engineering, Robotics, Mechatronics or a related field with a graduation date between 2026 - 2027 Strong engineering fundamentals and ability to perform first-principles analysis to ensure a successful design (stress-strain, thermal, tolerance, cost and mass optimization, etc.) Demonstrated ability to guide structural, sensing, thermal, and mechanism designs through CAE, from concept to mass production, across robotics, automotive, and consumer electronics Proficiency in CAE Tools such as BETA CAE, LS-DYNA, Abaqus, ADAMS, COMSOL, OPTISTRUCT, Design Life, FE Safe Exposure in building high-fidelity FE models at component, sub-system, and full-system levels Proficiency in linear and non-linear static, dynamic and modal simulations and experience developing multi-physics simulation workflows (e.g., thermal-mechanical, mechanical-electrical) Advanced knowledge in material characterization and modeling, including nonlinear elasticity, viscoelasticity, creep, and strain-rate dependent plasticity in Metals, Plastics, Polymers and Adhesives Strong programming and data analysis skills in MATLAB, Python, or equivalent