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Motorsports Competition - Performance Integration Engineer

  • Ubicación
    • Concord, North Carolina
  • Cronograma Full time
  • Publicado

Descripción

Hybrid: Position does not require an employee to be on-site full-time, but the general expectation is that the employee be onsite an average of three (3) days each week.

The Role

The GM Motorsports Program is seeking a Performance Integration Engineer to promote integration and collaboration across multiple engineering groups with a focus on ensuring that learnings are transferred across groups, improvements are uniformly implemented, and processes standardized. The Performance Integration Engineer will specifically coordinate between simulation, aero development, and tire scaling groups to establish standards for DIL (driver in the loop) simulator testing and desktop simulations. A portion of the role will encompass setting DIL test plans, developing and running simulations, and correlation of simulation models to physical, on-track performance. You will also identify future areas of focus for modeling improvement and work with internal GM groups to both validate solutions and implement these in production processes.

What You’ll Do

Collaborate with internal GM groups and GM supported teams to coordinate simulation approach and uniformly implement the latest modeling and process improvements developed by GM motorsports groups:

  • Regularly communicate with internal and external parties

  • Remain informed of latest advances within each GM department

  • Relay newest findings, current areas of development, and updates to tools/processes to all relevant groups, internal and external

  • Actively participate in team DIL sessions to ensure understanding of standard practices and identify areas of correlation discrepancy requiring future investigation

Continuously strive to improve GM Motorsports program methods and vehicle dynamics understanding by:

  • Globally approaching correlation questions

  • Critically assessing areas of deviation between modeling output and on-track performance

  • Road mapping solutions to problem areas and working together with each GM internal group to develop and implement solutions

  • Performing simulation studies and in-depth analysis of logged track data and driver feedback.

  • Actively seeking feedback from teams and drivers

  • Guiding Post-Race and Post-Test DIL sessions through working with all parties to establish objectives, identify laps for correlation, and prep simulation models

  • Documenting DIL and simulation activity/advances through contributions to regular Performance Group reports

#LI-LP2

[Additional Description]

Your Skills & Abilities (Required Qualifications)

  • Bachelor’s Degree in Engineering, Physics, or related subject

  • 5+ years of experience in a top-level motorsports series including NASCAR, IMSA, F1, IndyCar, WEC, or similar

  • Intimate knowledge of simulation workflows in a professional motorsports organization including both offline simulation and the DIL simulator; Experience using simulation tools to optimize vehicle performance

  • Proficient programing in Python, MATLAB, or similar language

  • Extensive experience analyzing on-track performance through both application vehicle dynamics principles and statistical methods

  • Strong organization skills, forward thinking mentality, and a superb attention to detail

  • Ability to multi-task in a dynamic, constantly evolving environment, with exceptional work ethic and integrity

What Will Give You a Competitive Edge (Preferred Qualifications)

  • Race Engineering experience with intimate knowledge of race car setup, event preparation, technical inspection, race procedures and race strategy

  • Proficiency in Motorsports data analysis software including Pi Toolbox, Atlas, Motec or similar

  • Knowledge and experience in tire modeling, construction, testing, and validation

  • Experience with aerodynamic testing and applying physical and/or CFD results to vehicle modeling tools for on-track performance optimization

  • Familiarity with vehicle testing methods and data reduction from on-track testing, SPMM, and 7-post

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