Motorsports Competition - IndyCar Performance Engineer

Description
Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Concord, NC three times per week, at minimum.
Given the need to support some live race events during weekends, this role will require the ability to work a flexible schedule.
The Role
This role will work within the GM Motorsports Performance Engineering group with a focus on supporting the IndyCar program. This group is responsible for driving on-track performance improvements through developing and implementing new motorsports analysis tools, guiding long-term vehicle development directions, and providing event specific vehicle configuration, setup, and strategy recommendations to supported race teams. Role responsibilities will span many disciplines requiring work in the areas of vehicle dynamics, data analytics, race strategy, as well as vehicle simulation model development, refinement, and correlation. Typical tasks will involve data reduction, correlation, and interpretation from on-track tests, rig tests, and DIL simulator sessions, vehicle simulation studies to identify areas for vehicle performance, and development and distribution of tools to assist teams and internal GM Motorsports groups in generating insights and efficiently finding conclusions.
An essential aspect of this role will be the effective collaboration with a range of internal GM Motorsports groups and external race teams partners to build understanding, understand needs and convey findings. and improve race team understanding to further effective application of GM motorsports work output and tools. This position will leverage resources across the GM Motorsports program to effectively develop program toolset and develop recommendations to increase the competitiveness of GM Motorsports IndyCar teams. This position will closely collaborate with the GM Motorsports Simulation group to develop and refine simulation tools and advance analysis methodologies. Coordination with GM production engineering, GM IT, GM Motorsports personnel, and GM race teams is essential in both developing underlying knowledge and implementing solutions.
What You'll Do
Assist GM IndyCar race teams in utilizing GM Motorsports toolchain and support race teams with vehicle performance insights:

• Mine prior event data for performance trends and characterize competitor performance by analyzing series-provided telemetry, timing and scoring data, and derived metrics from GM Motorsports race strategy tools.
• Utilize vehicle simulation tools, both offline and DiL simulator, to characterize event specific sensitivities and derive favorable vehicle configuration directions and setup recommendations. Investigations will likely begin with large simulation batches/DOEs, followed by targeted application of desktop sims and finalized by Driver in Loop (DiL) assessment.

• Support race teams and other GM Motorsports engineers in setup and use of Driver in Loop (DiL) simulators
• Develop race team understanding of simulation toolchain functionality and best modeling and analysis practices
• Correlate vehicle models, comparing logged track data with model output and develop relationships between performance and handling metrics and driver-perceived vehicle behavior. Fit collected data and develop inputs for simulation modeling.
• Convey findings in regular written reports distributed to GM IndyCar Teams.
• Actively review quality of correlation, accuracy of previous recommendations, and process bottlenecks/weaknesses to identify areas of future enhancement. Conceptualize and develop methods improvements and new tools to address identified issues and add value to customer race teams.
• Provide engineering support for rig and track tests, developing test plans, performing data analysis, and teaching team personnel to use tools and interpret simulation output.
• Travel to occasional IndyCar events to support at-track engineering efforts.

Build GM Motorsports program, by furthering global performance initiatives and transferring knowledge of team learnings and improved analysis methods across the GM motorsports group.

• Collaborate with Performance group members supporting other series to transfer learnings and adopt most useful analysis and reporting methods developed across the group.
• Represent race teams as a stakeholder in the simulation toolchain development process.

• Brainstorm new ways of achieving greater performance in targeted areas. Reimagine and prototype new and better solutions to common problems or questions.
• Coordinate with other internal GM Motorsports groups to share information, build knowledge base, and assist in collaboratively advancing support program. Provide recommendations consolidating the newest findings across the GM Motorsports groups to supported IndyCar teams.

#LI-LP2
Additional Description
What You'll Need (Required Qualifications)

• Bachelor's Degree in Engineering, Physics, Mathematics or related subject
• 5+ years of experience in a top-level motorsports series including IndyCar, F1, NASCAR, IMSA, WEC, or similar
• Intimate knowledge of simulation workflows in a professional motorsports organization i ncluding offline simulation and DIL
• Demonstrated experience using simulation tools to optimize vehicle performance
• Proficient programing in python, MATLAB, or similar language
• Experience analyzing on-track performance, defining performance metrics, and deriving actionable recommendations through application vehicle dynamics principles and statistical methods
• Highly analytical, detail oriented, customer focused, with positive relationship and strong communicative skills
• This job may be eligible for relocation benefits

What Will Give You a Competitive Edge (Preferred Qualifications)

• Master's Degree in Engineering, Physics, or related subject
• Software development experience with C#, WPF, or similar languages
• Race Engineering experience in IndyCar, F1, or Formula E 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
• Strong knowledge of high-performance vehicle, tire, and aero simulation modeling techniques

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