Damage Modeler - OnsiteJob SummaryGM Performance Power Units is seeking a highly motivated
Damage Modeler to support the development, testing, and trackside operations of our Formula 1 Power Unit. Based in Concord, North Carolina, this role offers a unique opportunity to contribute to a foundational area of our F1 program and assist in building a world-class reliability team. The Damage Modeler will sit at the intersection of materials science, structural mechanics, and F1 operational data. The Damage modeler will work within the Reliability group and interact closely with design, materials, and reliability experts to ensure that component life predictions are grounded in rigorous mechanics and real-world operating evidence, leading to race wins for our advanced hybrid power unit, targeted for debut with the Cadillac F1 Team.
Key ResponsibilitiesDamage Model Development & Maintenance- Develop, validate, and maintain physics-based damage accumulation models for all life-critical PU components, covering LCF, HCF, creep, TMF, and combined damage interaction mechanisms.
- Define and maintain material fatigue and creep databases for PU-relevant alloys, incorporating both published material data and GM PPU test-derived values as the program matures.
- Apply established damage accumulation frameworks and assess their applicability and conservatism against observed field evidence, refining models accordingly.
Component Life Prediction & Duty Life Definition- Produce component duty life predictions from first principles, translating FEA stress/strain outputs, thermal analyses, and operational load spectra into quantitative life consumption estimates with associated uncertainty bounds.
- Define and maintain the operational duty life limits for all regulated and reliability-critical PU components, providing the engineering basis for the component life budgets used by the reliability team and the parts analyst throughout the season.
- Update life predictions continuously as in-season operating data, teardown evidence, and dyno test results expand the empirical basis for each model, maintaining a living lifing document set that reflects the current state of knowledge.
Load Spectrum Development & Operational Data Integration- Develop representative load spectra for PU components by processing operational data from ATLAS telemetry using cycle-counting and signal processing methods to characterize the damage-relevant content of each operating environment.
- Work with the Reliability Data Engineer to establish automated data pipelines that continuously update load spectrum inputs from dyno and race telemetry, reducing the lag between operational evidence and updated life predictions.
- Identify and quantify differences in damage severity across operating environments to ensure life budgets reflect the most damaging credible usage profile.
Failure Investigation & Model Correlation- Contribute to failure investigations by applying damage modeling perspective to assess model fidelity and identify whether failures are consistent with, or diverge from, model predictions.
- Use failure and teardown evidence to calibrate and improve damage models over time, creating a structured feedback loop between physical observations and analytical predictions that continuously increases model confidence.
Cross-Functional Collaboration & Design Support- Partner with design engineers during new component development to provide life prediction input at gate reviews, identifying life-critical features, stress concentrations, and material choices that will determine duty life margins before hardware is committed to production.
- Support FMEA processes by providing quantitative damage-based risk input - translating uncertainty in load, material, and geometry assumptions into probabilistic life estimates that inform risk prioritization.
- Communicate life prediction results clearly to the broader reliability team, design organization, and program leadership, including explicit discussion of model assumptions, confidence levels, and the sensitivity of predictions to key input uncertainties.
Required Qualifications- Bachelor's degree in Mechanical Engineering, Automotive Engineering, Aerospace Engineering, or a closely related engineering discipline with a strong emphasis on structural mechanics, fatigue, or fracture mechanics.
- 5+ years of engineering experience in a structural integrity, lifing, fatigue, or damage tolerance role - ideally within motorsport or high-performance automotive.
- Demonstrated hands-on experience developing or applying damage models to predict fatigue or creep life of real hardware operating under complex, multi-mechanism loading conditions.
- Prior experience correlating analytical life predictions against physical test or field failure evidence, and iteratively improving models on the basis of that correlation.
Technical Skills- Deep knowledge of fatigue and damage mechanics: Low-Cycle Fatigue(LCF), High-Cycle Fatigue(HCF), creep, Thermomechanical Fatigue(TMF), and combined-mechanism interaction - including the theoretical basis of each and their relative significance for different PU component types and operating regimes.
- Proficiency in FEA tools (Abaqus, ANSYS, or equivalent) for stress/strain extraction from complex component geometries under thermal and mechanical loading; ability to critically interpret FEA outputs for lifing purposes.
- Experience with cycle-counting methods and load spectrum development from time-history operational data.
- Familiarity with fracture mechanics principles and crack propagation analysis (NASGRO, AFGROW, or equivalent) as applied to remaining life assessment.
- Proficiency in Python or MATLAB for scripting damage calculation routines, processing large telemetry datasets, and automating life prediction workflows.
- Working knowledge of metallic materials commonly used in high-performance engines and their fatigue and creep behavior at elevated temperatures.
Interpersonal & Organizational Skills- Able to communicate complex analytical results with appropriate nuance to both engineering peers and non-specialist stakeholders.
- Intellectually rigorous and comfortable defending analytical conclusions under scrutiny from experienced engineers.
- Able to manage multiple concurrent lifing analyses across different components and development phases in a fast-moving program environment.
Preferred Skills- Prior experience in an F1 or top-tier motorsport PU environment.
- Master's degree or PhD in Mechanical Engineering, Aerospace Engineering, or Materials Science.
- Experience with probabilistic life prediction methods applied to safety-critical rotating components.
- Familiarity with TMF testing and model development for high-temperature alloys.
- Experience processing and interpreting F1 or motorsport PU telemetry data using ATLAS or equivalent platforms to extract damage-relevant load history content.
- Background in developing or applying creep-fatigue interaction models (e.g., strain range partitioning, frequency-modified methods) to hot-section components.
- Knowledge of FIA Technical Regulations as they pertain to PU component specifications and homologation - sufficient to understand the regulatory context within which life predictions must be made and defended.
You'll play a pivotal role in ensuring the reliability and performance of a next-generation Formula 1 power unit. Our culture rewards precision, innovation, and the relentless pursuit of performance.
Only direct hires need apply to or inquire about job postings at GM Performance Power Units. We are not accepting calls, resumes or applications from recruiting firms at this time. 
