Engine Calibration Methodology Engineer

StellantisAuburn Hills, MI

About The Position

Engine Calibration Engineer supports development, validation, and continuous improvement of model-based and physics-based calibration methods across ICE, xHEV, and BEV applications. This early-career role assists methodology development, data analysis, model correlation, validation planning, and process documentation, helping calibration teams improve repeatability, quality, efficiency, range, fuel economy, drivability, and emissions readiness.

Requirements

  • BS in Engineering or related field.
  • Experience in engine system development, calibration, controls, model-based development, or physics-based modeling preferred.
  • Prior experience in base engine dyno calibration on boosted/TJI engines.
  • Knowledge of ICE subsystems: combustion, valvetrain, fuel system, boost, EGR, aftertreatment.
  • Data acquisition experience collecting, processing, and organizing dyno, vehicle, HIL, or virtual test data.
  • Working knowledge of engine analysis/calibration tools, emissions development, and engine technologies.
  • Basic proficiency in MATLAB/Simulink to support model-based analysis and calibration methodology.
  • Good teamwork and independent-work skills; effective communication and clear documentation habits.

Nice To Haves

  • Master's degree in engineering.
  • Experience with engine dynamometer measurement systems, data acquisition, and data analytics.
  • Work experience in spark ignition engine controls and calibration.
  • Experience with DOE, engine modeling, neural networks, reactive problem solving, or statistics.
  • Exposure to Model Advisor/MXAM, Simulink Requirements, MDS, SystemDesk, RTC/RQM, DNG, or related model-quality tools.

Responsibilities

  • Support gasoline base calibration methodology (torque model, spark, knock, combustion, airflow, fuel, boost, VVT, EGR, idle, startability) plus SS Emissions, Off-Nominal, and Transient calibration.
  • Support release-readiness checklists, dataset maturity evidence, and organized documentation for calibration freeze and program milestones.
  • Support model-based/physics-based methods by documenting inputs, assumptions, limitations, and validation evidence; assist building/improving virtual models.
  • Support correlation of vehicle, dyno, HIL/SIL/MIL, and virtual datasets to identify simulation-to-physical gaps.
  • Use MATLAB, Simulink, ETAS INCA, MDA, dSPACE Automation, and ControlDesk to support data analysis and methodology work.
  • Support structured root-cause analysis, data summaries, and lessons-learned capture for calibration issue resolution.
  • Support validation/test planning (dyno, vehicle, HIL/SIL/MIL, virtual) and calibration maturity/readiness assessments.
  • Collaborate with CoE, Controls, Emissions, Validation, and application calibration teams; help document and improve methodology and best practices.
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