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.
The Role
This position is part of the GM Motorsports Performance Engineering team, with a primary focus on supporting the IndyCar program. Our mission is to maximize on-track performance by developing and deploying advanced motorsports analysis tools, shaping long-term vehicle development strategies, and delivering event-specific recommendations for vehicle configuration, setup, and race strategy to our partner teams. In this role, you will work across multiple disciplines, including vehicle dynamics, data analytics, race strategy, and simulation model development, refinement, and correlation. Your contributions will directly influence competitive performance and innovation within the IndyCar program.
Typical responsibilities include reducing, correlating, and interpreting data from on-track tests, rig evaluations, and Driver-in-the-Loop (DIL) simulator sessions; conducting vehicle simulation studies to identify performance opportunities; and developing and distributing tools that enable race teams and internal GM Motorsports groups to generate actionable insights and reach conclusions efficiently.
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. As well as improving race team understanding to further effective application of GM motorsports work output and tools. You will leverage resources across the GM Motorsports program to effectively develop toolsets and develop recommendations to increase the competitiveness of GM Motorsports IndyCar teams. You 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:
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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.
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Convey findings in regular written reports distributed to GM IndyCar Teams.
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Develop race team understanding of simulation toolchain functionality and best modeling and analysis practices
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Support race teams and other GM Motorsports engineers in setup and use of Driver in Loop (DiL) simulators
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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.
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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.
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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.
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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.
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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.
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Collaborate with Performance group members supporting other series to transfer learnings and adopt most useful analysis and reporting methods developed across the group.
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Represent race teams as a stakeholder in the simulation toolchain development process.
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Brainstorm new ways of achieving greater performance in targeted areas. Reimagine and prototype new and better solutions to common problems or questions.
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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.
What You'll Need (Required Qualifications)
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Bachelor’s degree in Engineering, Physics, Mathematics or related subjects
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5+ years of experience in a top-level motorsports series including IndyCar, F1, NASCAR, IMSA, WEC, or similar
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Intimate knowledge of simulation workflows in a professional motorsports organization i ncluding offline simulation and DIL
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Demonstrated experience using simulation tools to optimize vehicle performance
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Proficient programing in python, MATLAB, or similar language
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Proficiency in Motorsports data analysis software including Pi Toolbox, Atlas, Motec or similar
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Experience analyzing on-track performance or simulation performance by defining performance metrics, and deriving actionable recommendations through application vehicle dynamics principles and statistical methods
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Highly analytical, detail oriented, customer focused, with positive relationships and strong communicative skills
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Given the need to support some live race events during weekends, this role will require the ability to work a flexible schedule
What Will Give You a Competitive Edge (Preferred Qualifications)
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Software development experience with C#, WPF, or similar languages
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Multi-body model development experience with Modelica/Dymola, MSC Adams, or similar
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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
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Strong knowledge of high-performance vehicle, tire, and aero simulation modeling techniques
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