Virtual Calibration Engineer for Vehicle Propulsion systems - ICE & Hybrid - São Caetano do Sul or Indaituba/SP

GM

10h • Hybrid

About The Position

This role will work hybrid model (3x onsite in Sao Caetano do Sul Office or Indaiatuba Office). Virtual Calibration Engineer – ICE & Hybrid Vehicles is a capability-focused role centered on using simulation-based methods to support calibration development for internal combustion and hybrid propulsion systems. The engineer builds and correlates 1D models in tools like GT-Power and uses MATLAB workflows to generate virtual calibration deliverables, improve performance prediction, and reduce dependence on physical dyno testing. Key scope: Develop and maintain engine/propulsion simulation models, Support early and mid-stage calibration deliverables, Work on calibration areas such as VE, torque model, spark, cam phaser, air estimation, and thermal models, Use DOE, ANN, and optimization workflows for analysis and model-based calibration. Profile sought: Supporting efficiency improvements in FRaPA testing, including reducing manual review, retests, dyno time, and post-processing effort through automation and data-driven methods. Strong analytical and problem-solving skills, Good technical curiosity and self-learning ability, Effective cross-functional collaboration and communication with local and global teams, Strong ownership, urgency, and delivery focus.

Requirements

• Degree in Mechanical, Automotive, Mechatronics, Controls, or related engineering
• Engine/Hybrid propulsion systems knowledge
• 1D Modeling, thermodynamics, combustion, controls, or hybrid systems
• Active CREA
• GT Power
• MatLab
• Office Package
• English Fluent

Nice To Haves

• Preferred additional systems knowledge in powertrain cooling /HVAC
• CFD Tools (desired)

Responsibilities

• Develop and maintain engine/propulsion simulation models
• Support early and mid-stage calibration deliverables
• Work on calibration areas such as VE, torque model, spark, cam phaser, air estimation, and thermal models
• Use DOE, ANN, and optimization workflows for analysis and model-based calibration
• Supporting efficiency improvements in FRaPA testing, including reducing manual review, retests, dyno time, and post-processing effort through automation and data-driven methods.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level