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Network Design Optimization Engineer Jobs (NOW HIRING)

GMPPU

ERS ML Design Optimization Engineer

Concord, NC · On-site

Formula 1 ERS ML Design Optimization Engineer Concord, NC, USA GM Performance Power Units (GM PPU ... Build neural network surrogates (e.g., PINNs, graph nets) emulating ERS physics across thermal ...

Acara Solutions

Network Design Engineer

Scottsdale, AZ · On-site

$66.59/hr

Senior Network Design Engineer Active Secret clearance is required at the time of hire Location ... and performance optimization. * Configure and support routers, switches, firewalls, servers ...

Kelly Services

Network Design Engineer

Waukesha, WI

$60 - $65/hr

Network Design Engineer Duration: 12-Month Contract (Potential for Temp-to-Hire) Location: 100 ... is optimized for performance. * Drive Innovation: Manage multiple high-stakes projects ...

Via Logic LLC

Senior Network Engineer

Laurel, MD · On-site

$106K - $146K/yr

Senior Network Engineer Leidos - National Security Sector | Cyber & Analytics Business Area Make an ... Strong experience in network design, optimization, and security * CCNA and CCNP certifications ...

Leidos

Network Design Engineer

Aurora, CO · On-site

$73K - $132K/yr

The Digital Modernization Sector at Leidos has an opening for a Design Engineer (Campus Area Network/Local Area Network (CAN/LAN)) to support our customer's global enterprise networks. The CAN/LAN ...

Belcan

Network Design Engineer

Waukesha, WI

$60 - $65/hr

Network Design Engineer Location: Waukesha, WI Zip Code: 53188 Duration: 12 Months Pay Rate: $60 -$65/hr. Shift: 8 to 5 pm EST Keyword's: #Waukeshajobs; #DesignEngineerjobs ; Start Date: Immediate We ...

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ERS ML Design Optimization Engineer

Concord, NC • On-site

GMPPU
See more jobs at GMPPUexternal

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Posted 8 days ago

Job description

Formula 1 ERS ML Design Optimization Engineer

Concord, NC, USA

Job Description

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.
  • Proficiency handling multi-fidelity datasets (real + DiL/HiL/SiL).
  • Familiarity with hybrid powertrains, multi-physics sim tools.
  • 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
  • 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.
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