Job Description

What Makes a Honda, is Who makes a Honda
Honda has a clear vision for the future, and it’s a joyful one. We are looking for individuals with the skills, courage, persistence, and dreams that will help us reach our future-focused goals. At our core is innovation. Honda is constantly innovating and developing solutions to drive our business with record success. We strive to be a company that serves as a source of “power” that supports people around the world who are trying to do things based on their own initiative and that helps people expand their own potential. To this end, Honda strives to realize “the joy and freedom of mobility” by developing new technologies and an innovative approach to achieve a “zero environmental footprint.”

We are looking for qualified individuals with diverse backgrounds, experiences, continuous improvement values, and a strong work ethic to join our team.

If your goals and values align with Honda’s, we want you to join our team to Bring the Future!

Job Purpose

As a senior member of the CAE Methods Department, you will be responsible to lead CAE method and process creation related to AL/ML for structural based CAE like strength, reliability, NVH, and crash worthiness. Proficient use of CAE contributes to improved optimization, speed, and efficiency of our products and development processes.

Key Accountabilities

• Lead a small team to develop and validate new CAE methods in the areas of AI/ML application to structural CAE problems.
• Lead collaboration with other CAE engineers to understand and document existing processes and requirements in order to accurately create the necessary AI/ML CAE methods. Effectively present analysis and information to technical experts.
• Create documentation that clearly explains the requirements, assumptions, setup, process, validation, and outputs of developed methods. Also clearly document the value added with the established method

Qualifications, Experience, and Skills

• BS in mechanical engineering. Advanced degree preferred.
• Minimum of five years experience
• Expertise with CAE software such as modeFRONTIER , and iSight to perform optimization and DOE studies. Familiarity with various CAE software such as Abaqus, Nastran, LS-Dyna, Hypermesh and Ansa are preferred. Also expertise with programming language software such as Python, Matlab, and Excel VBA. 
• Understanding of Reduced Order Models (ROM), Response Surface Models (RSM), and Neural Networks. 
• Extensive experience with creation of new CAE Methods and performing verification and validation. 
• Ability to breakdown complex concepts into simple summaries
• Excellent communication and interpersonal skills

Working Conditions

• Work is primarily conducted at an office desk. Some time is spent at test facilities for collaboration.
• Hybrid (office/home) work is available.
• Travel and overtime are occasionally required.

What differentiates Honda and make us an employer of choice?

Total Rewards:

• Competitive Base Salary (pay will be based on several variables that include, but not limited to geographic location, work experience, etc.)
• Paid Overtime
• Regional Bonus (when applicable)
• Industry-leading Benefit Plans (Medical, Dental, Vision, Rx) 
• Paid time off, including vacation, holidays, shutdown
• Company Paid Short-Term and Long-Term Disability 
• 401K Plan with company match + additional contribution
• Relocation assistance (if eligible)

Career Growth:

• Advancement Opportunities
• Career Mobility
• Education Reimbursement for Continued Learning
• Training and Development programs 

Additional Offerings:

• Tuition Assistance & Student Loan Repayment
• Lifestyle Account
• Childcare Reimbursement Account
• Elder Care Support
• Wellbeing Program
• Community Service and Engagement Programs
• Product Programs

Honda is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, creed, religion, national origin, sex, sexual orientation, gender identity and expression, age, disability, veteran status, or any other protected factor.

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