Staff Engineer — Virtualization, Knowledge Management & Agentic Simulation

Job Description

At General Motors our product teams are redefining mobility. Through a human-centered design process we create vehicles and experiences that are designed not just to be seen but to be felt. Were turning todays impossible into tomorrows standard from breakthrough hardware and battery systems to intuitive design intelligent software and next-generation safety and entertainment features.

Every day our products move millions of people as we aim to make driving safer smarter and more connected shaping the future of transportation on a global scale.

The Role

Lead the development of agentic simulation frameworks AI-driven knowledge management systems and virtualization strategies for complex engineering environments. This role emphasizes performance validation methodologies predictive analytics for AI tool efficacy and advanced simulation orchestration.

What Youll Do

Agentic Simulation Frameworks

• Architect multi-agent workflows for design analysis and decision-support.
• Implement orchestration strategies for parallel and serial agent execution.
• Integrate AI agents for requirement verification optimization and adaptive learning.

AI Knowledge Management

• Deploy Validation strategies for authenticating synchronization and optimizing organizational knowledge.
• Design Knowledge Management (KM) pipelines across multiple platforms and develop predictive models for AI tool efficacy.
• Validate KM systems through large-scale multi-agent simulations.

Virtualization & Simulation Performance

• Develop virtualization strategies for scalable simulation environments.
• Conduct performance analysis: throughput latency determinism resource utilization and robustness under stress.
• Apply statistical validation frameworks to ensure reproducibility and confidence in simulation results.

Validation Methodologies

• Establish quantitative metrics for simulation fidelity and decision-making efficiency.
• Implement predictive analytics for AI deployment success using A/B testing offline replay and sensitivity analysis.
• Document validation evidence for enterprise-scale rollouts.

Your Skills & Abilities (Required Qualifications)

Education

• PhD or Masters degree in Electric Engineering Computer Engineering or related field.
• Professional education in Modeling and Simulation (NTSA or alike)
• Professional education in Software quality and testing (ISTQB QAIs CSTE/CSQA or STEC)
• 10 years of experience delivering embedded or system-level software in production environments.

Agentic Simulation

• Experience designing multi-agent architectures and orchestration patterns.
• Experience with agent-based modeling frameworks and collective intelligence optimization.

AI Knowledge Management

• Expertise in validation frameworks knowledge capture and efficiency metrics.
• Ability to predict and validate AI tool efficacy using simulation and statistical methods.

Performance Validation

• Strong background in simulation performance benchmarking: latency determinism scalability and robustness.
• Proficiency in statistical validation (confidence intervals effect sizes hypothesis testing).
• Strong background with high-performance high-fidelity control systems simulation for Electric Drive Power Electronics and RESS

Software & Tools

• Programming: MATLAB/Simulink Python C for simulation control data analysis and ML integration.
• AI/ML: PyTorch TensorFlow scikit-learn for predictive modeling.
• Data Analysis: NumPy Pandas SciPy visualization with Matplotlib Seaborn.
• Experiment Tracking: MLflow Airflow Prefect.
• CI/CD: Git GitLab Jenkins containerization with Docker/Kubernetes.

Performance Analysis Tools

• Profilers: Perf VTune Nsight Systems for CPU/GPU utilization.
• Timing & Jitter Analysis: Chrony Perfetto Trace Compass.
• Resource Monitoring: Prometheus/Grafana htop nmon.
• Statistical Analysis: R SciPy Statsmodels for hypothesis testing and confidence metrics.

What Will Give You a Competitive Edge (Preferred Qualifications)

• Demonstrated success in deploying AI-driven KM systems with measurable efficiency gains.
• Experience validating simulation frameworks under stress and scalability scenarios.
• Proven ability to forecast AI tool performance using predictive analytics and simulation-based testing.

About GM

Our vision is a world with Zero Crashes Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day individually and collectively to drive meaningful change through our words our deeds and our culture. Every day we want every employee to feel they belong to one General Motors team.

Benefits Overview

From day one were looking out for your well-beingat work and at homeso you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex race color national origin citizenship status religion age disability pregnancy or maternity status sexual orientation gender identity status as a veteran or protected veteran or any other similarly protected status in accordance with federal state and local laws.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required where applicable to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more visit How we Hire.

Accommodations

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