| Position | Formula 1 ERS ML Design Optimization Engineer |
| Posted | 01 Jul 2026 |
| Expired | 31 Jul 2026 |
| Company | GM Performance Power Units |
| Location | Concord | GB |
| Job Type | Full Time |
Latest job information from GM Performance Power Units for the position of Formula 1 ERS ML Design Optimization Engineer. If the Formula 1 ERS ML Design Optimization Engineer vacancy in Concord matches your qualifications, please submit your latest application or CV directly through the updated Jobkos job portal.
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GM Performance Power Units - Concord, NC
ERS ML Design Optimization Engineer - Onsite
Job Summary
GM Performance Power Units (GM PPU) seeks an ERS ML Design Optimization Engineer to join our team in Concord, NC. This role leverages ML for design optimization, simulation acceleration, and performance analysis of ERS systems (MGU-K, CU-K, ES) using telemetry and physics-based data. Focus on surrogate models to reduce sim cycles while meeting FIA constraints.
Key Responsibilities:
• Build neural network surrogates (e.g., PINNs, graph nets) emulating ERS physics across thermal, electrical, degradation behaviors.
• Implement tool-agnostic GA/BO optimization loops for multi-objective ERS design (mass/power/reliability).
• Fuse/process petabyte-scale datasets from bench/dyno/track + DiL/HiL/SiL sims for training/validation.
• Conduct sensitivity analysis, uncertainty quantification on ERS parameter spaces.
• Develop ML-accelerated workflows integrated with NX/AVL/MATLAB/ANSYS sim chains.
• Validate models against real duty cycles; iterate for FIA-constrained optima.
• Document optimization pipelines, neural architectures, and results for design reviews.
Required Qualifications:
• Bachelor's in CS/EE/Math/Physics; Master's/PhD in ML/scientific computing preferred.
• 3+ years building neural surrogates for engineering sims; GA/BO optimization experience.
• Expert in PyTorch/TensorFlow/JAX; large-scale time-series/physics data pipelines.
• Proficiency handling multi-fidelity datasets (real + DiL/HiL/SiL).
• Familiarity with hybrid powertrains, multi-physics sim tools.
Desirable Skills:
• F1 ERS plant modeling (cell/MGU/ES performance prediction).
• Neural operators/PINNs for PDE surrogates; multi-fidelity BO.
• HPC workflows, data versioning (DVC), containerization.
• Domain expertise in e-motors, batteries, power electronics.
Personal Attributes:
• Delivers under aggressive development timelines.
• Innovates across model/design/compute trade-offs.
• Communicates complex ML insights to design engineers.
• Rigorous validator of sim fidelity against reality.
• Passionate about F1 performance engineering.
Why Join Us
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.
Please note: GM Performance Power Units and all affiliated companies are Equal Opportunity employer(s). Minorities, women, veterans, and individuals with disabilities are encouraged to apply. For more information regarding the EEOC, please visit
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.
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