Combustion System Analysis Engineer

GM Performance Power Units•Concord, NC

1d•Onsite

About The Position

The Combustion System Analysis Engineer is responsible for the definition of GMPPU’s combustion chamber surfaces, ensuring that combustion chambers, ports, valvetrain layouts, and pistons deliver optimal performance and efficiency. This role uses parametric CAD tools and 3D CAE in close collaboration with design, mechanical simulation, and testing teams to conceptualize and iterate upon the combustion chamber geometry. The engineer provides the optimized geometries and performance metrics needed for single‑cylinder and multi‑cylinder development, and acts as a key technical interface between other analytical, test, design, and hardware teams.

Requirements

Bachelor of Science in Mechanical Engineering, Automotive Engineering, Aerospace Engineering, or related field.
5+ years of experience in engine design, combustion system design, or closely related powertrain hardware development.
Strong understanding of combustion fundamentals, thermodynamics, fluid mechanics, and engine airflow principles.
Proficiency with 3D simulation tools and using their outputs to guide design decisions (CONVERGE, Star‑CCM+, or equivalent).
Experience with 3D CAD tools (e.g., NX, CATIA, or similar) for complex surface modeling.
Demonstrated ability to manage multiple design concepts and trade‑offs under timing and packaging constraints.
Effective oral and written communication skills, including preparation of clear design documentation and technical presentations.
Strong collaboration and interpersonal skills, able to work across functions (design, analysis, development, manufacturing).

Nice To Haves

Master’s degree or PhD in Mechanical/Automotive/Aerospace Engineering with emphasis on IC engine combustion or fluid dynamics.
8+ years of experience in engine or combustion system design and analysis for high‑performance race engines.
Hands‑on experience with single‑cylinder engine testing and interpretation of combustion/airflow results as feedback to design.
Expert knowledge of 3D CFD simulation and post‑processing for in‑cylinder flow and combustion.
Experience with design optimization, machine learning/AI optimization, and DOE methodsDemonstrated contribution to design standards, manuals, or training related to combustion or airflow systems.

Responsibilities

Combustion System Concept Generation
Own the definition of the combustion chamber surfaces (chamber shape, piston crown, intake/exhaust ports, valve angles and layout, injector and ignition locations, squish regions, etc.)
Use parametric CAD tools and standardized methods to rapidly generate, modify, and compare alternative combustion system concepts within design and manufacturing constraints.
Work with engine architecture teams to ensure bore, stroke, compression ratio, and valvetrain concepts are compatible with combustion and airflow requirements.
Analysis, Simulation, and Metrics
Collaborate with 1D performance analysts and 3D CFD engineers to assess airflow, charge motion, mixture preparation, and combustion quality for candidate designs.
Utilize high‑quality surface models and meshes of chambers, ports, and pistons for mixing and combustion CFD, and iterate designs based on analysis results.
Establish and track combustion system scorecards and metrics (e.g., flow coefficients, homogeneity, charge motion, valve area, geometric constraints) to rank and down‑select concepts.
Support correlation between virtual predictions and single‑cylinder/multi‑cylinder test data, refining designs to close gaps in performance or efficiency.
Cross‑Functional Collaboration & Methods
Interface closely with design, 1D/3D CAE, mechanical simulation, calibration, and vehicle integration teams to align on requirements, boundary conditions, and trade‑offs.
Establish and maintain combustion system design methodologies, templates, and standard work, including parametric libraries and best practices.
Present design options and recommendations to technical specialists and program leadership in clear, data‑driven reviews.