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Robotics CAE Engineer, Optimus

Tesla
Langley, BC

Postuler dès maintenant

Détails du poste

Temps plein

Compétences

Génie mécanique
MATLAB
Ingénierie
Ingénierie mécanique
Analyse de données
Robotique
Compétences en communication
Python

Description complète du poste

What to Expect

The Tesla Robotics Team designs and builds humanoid bi-pedal robots (Optimus) to perform tasks that are boring, repetitive, and dangerous for humans. As a CAE Engineer, 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.

What You'll Do

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

What You'll Bring

Degree in Mechanical Engineering or a related field, or equivalent experience
Strong foundation in Engineering Mechanics, Computational Mechanics, Material Science, and Finite Element Theory and applications
Demonstrated ability to guide structural, sensing, thermal, and mechanism designs through CAE, from concept to mass production, across robotics, automotive, and consumer electronics
Expertise 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
Proficiency in CAE Tools such as BETA CAE, LS-DYNA, Abaqus, ADAMS, COMSOL, OPTISTRUCT, Design Life, FE Safe
Strong programming and data analysis skills in MATLAB, Python, or equivalent
Excellent communication and interpersonal skills with the ability to collaborate effectively across cross-functional teams

Tesla is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state or local laws.

Tesla is also committed to working with and providing reasonable accommodations to individuals with disabilities. Please let your recruiter know if you need an accommodation at any point during the interview process.

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python emplois - mission, bc

Robotics CAE Engineer, Optimus

Lead Test Engineer

Principal PIC Design Engineer

Principal Engineer, Optics Engineering

Senior Software Engineer / Technical Lead – Research Platform (Rust + Python)

Experienced Quantitative Analyst

Conseiller(ère) en intégration de données FME

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