Engineering Group Manager – Electrical Integration, Numerical Optimization

Jobtailor

Missouri

On-site

USD 140,000 - 170,000

Full time

14 days+

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Job summary

General Motors is seeking a senior engineer to drive cross-functional vehicle development through advanced optimization of electrical packaging and physical integration. You will lead the design and implementation of optimization toolchains, balancing cost, mass, and manufacturability to accelerate iterative development.

The role requires expertise in numerical optimization, Python/C++ programming, and CAD/CAE integration, with a track record of leading cross-functional teams in vehicle

Qualifications

Bachelor's degree in computational science, engineering or related field.
Experience leading development and application of numerical optimization tools.
Proficiency in Python, SciPy, NumPy, Pyomo.
Experience with CAD/CAE tools and plugin scripting.
8+ years of engineering experience in a technical environment.
Strong ability to lead cross-functional teams in vehicle packaging.

Responsibilities

Drive cross-functional and high-impact areas of vehicle development.
Develop and apply optimization of physical product layout under constraints like space, geometry, wiring rules, assembly efficiency, and serviceability.
Build advanced toolchains, methods, and processes for rapid design optimization.
Optimize total enterprise cost across architectures and programs.
Lead cross-functional collaboration to align electrical and architectural systems.

Skills

Numerical Optimization

Python Proficiency

C++ Proficiency

Cross-Functional Collaboration

Leadership

Analytical Capabilities

CAD/CAE Integration

Electrical Architecture

Education

Bachelor's degree or higher in Computational Science / Engineering / Mathematics

Tools

SciPy

NumPy

Pyomo

Ansys

Abaqus

SolidWorks

OpenFOAM

Job description

You will drive one of the most cross-functional and high-impact areas of vehicle development at General Motors.
Develop and apply computer-driven optimization of physical product layout/design under real constraints like space, geometry, wiring rules, assembly efficiency, and serviceability.
Build advanced toolchains, methods, and processes that enable rapid optimization of design, packaging, and integration at the speed required for iterative development.
Optimize total enterprise cost across architectures and programs.
Optimize packaging for a given set of modules.
Inform the design of future electrical architectures.
Lead cross-functional collaboration and drive architecture and program development by laying out the electrical system alongside critical architectural systems such as body structure, propulsion, occupant package, and studio theme.
Shape advanced vehicle development by improving electronics packaging strategies that reduce wiring harness cost, complexity, and downstream tradeoff inefficiencies.
Develop expertise and standards in critical areas such as post-crash electrical integrity, network design, electrical redundancy, manufacturing assembly processes, module flashing, and sequencing for efficient installation.
Drive operational excellence by balancing cost, mass, assembly effort, manufacturing sequencing, and quality to achieve world-class integration and efficiency.
Set the vision for the organization to drive speed and innovation in electrical packaging and physical integration, enabling industry leading vehicles that are smarter, safer, and more cost-efficient.

Demonstrates expertise in Numerical Optimization techniques and Engineering Frameworks, with proficiency in Python, C++, and CAD/CAE integration. Capable of leading cross-functional teams to optimize vehicle electrical architectures and packaging strategies for enhanced efficiency and cost-effectiveness.

Requirements

Bachelor's degree (or higher) in Computational Science, Engineering and Mathematics, Operations Research & Industrial Engineering, Applied Mathematics, Engineering, Computer Science, Physics, or other relevant disciplines.
Applicable experience in leading development and application of tools: Numerical Optimization: Experience with algorithms like Gradient Descent, Genetic Algorithms, SQP (Sequential Quadratic Programming), or MDO (Multidisciplinary Design Optimization). They should know when to use a gradient-based solver versus a global, derivative-free heuristic.
Engineering Frameworks & Languages: Proficiency in Python (SciPy, NumPy, Pyomo), C++ (for performance-critical solvers), or MATLAB/Simulink. Experience with Julia is also a huge plus in modern scientific computing.
CAD/CAE Integration: Experience writing plugins, scripts, or standalone tools that interact with commercial engineering software (like Ansys, Abaqus, SolidWorks, or OpenFOAM) via APIs.
8+ years of engineering experience in a technical environment with strong analytical capabilities.
Ability to pull together total enterprise solutions and recommendations for programs.
Proven leadership experience in vehicle execution and total vehicle physical packaging, including experience using computer aided drafting software.
Experience with post-crash electrical integrity requirements, assembly sequencing optimization, module flashing, and network design and balancing.

Core Competencies

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