Job Description
Job Description We are the movers of the world and the makers of the future. We get up every day, roll up our sleeves and build a better world -- together. At Ford, we’re all a part of something bigger than ourselves. Are you ready to change the way the world moves? In this position... Join Ford as an In-Vehicle Network Performance Architect. In this individual contributor role, you will own the vision, standards, and operating model for network performance modeling and continuous performance insight across complex Ethernet/CAN-FD/LIN vehicle networks. You will build and maintain high-fidelity models to predict latency/jitter/utilization and coupling, run data-driven studies that shape architecture decisions, forecast lifecycle growth, and use SIL/HIL/vehicle data pipelines and dashboards to detect and respond to emerging performance risks during development Ford’s Network Architecture organization is advancing faster, data-driven end-to-end network thinking that unifies software, hardware, and platform programs. As the In-Vehicle Network Performance Architect, you will act as the technical product owner for Ford’s network performance modeling and monitoring capability—defining “what good looks like,” standardizing methods, and ensuring the right performance insights are produced at the right time in the systems engineering and architecture lifecycle. This role blends architecture/systems engineering judgment with real-world complex network performance analysis. The ideal background may come from automotive or adjacent domains (defense, aerospace, networking/IT, distributed systems), but must include experience with vehicle communications (Ethernet, CAN/CAN-FD, LIN). Responsibilities What you'll do... Product Ownership for Network Performance Modeling & Insight Own the vision, roadmap, and standard work for network performance modeling, simulation, and integration-time monitoring across vehicle programs. Define performance modeling “contracts”: assumptions, required inputs, model fidelity tiers, scenario libraries, calibration approach, and output formats for decision-making. Establish and track adoption KPIs (coverage, turnaround time, prediction accuracy, regression detection time). High-Fidelity Modeling & Simulation Build and maintain high-fidelity simulation and analytical models to predict network latency, jitter, utilization, congestion behavior, and coupling across mixed Ethernet/CAN-FD/LIN topologies. Ensure models reflect real architectural complexity (gateway effects, contention, burstiness, protocol overheads, scheduling/priority behaviors, growth in variants/features). Data-Driven Studies to Drive Architectural Shifts Participate in quantitative trade studies to recommend architectural changes (topology, bandwidth allocation, segmentation strategies, gateway strategy, timing/priority strategies). Produce decision-ready outputs: expected deltas, confidence level, sensitivities, risks, and clear mitigation options. Lifecycle Forecasting: Bus Load & Memory Utilization Create forecasting models to project bus load/bandwidth headroom and memory utilization over the vehicle lifecycle. Define growth envelopes and triggers so the architecture remains viable as future features/services expand. Integration-Time Performance Monitoring & Rapid Response Define and drive the approach to monitor trends during development/integration using SIL/HIL/vehicle logs and dashboards. Build/enable a closed-loop system: model predictions ↔ integration measurements ↔ updated assumptions/calibration. Lead rapid performance investigations (root-cause hypotheses, targeted analyses, recommended corrective actions) when programs hit latency/jitter/utilization/coupling issues. Embed Performance into the Systems Engineering Lifecycle Integrate network performance artifacts into architecture and change-control workflows: performance budgets, guardrails, regression checks, and sign-off criteria. Represent network performance in technical reviews and governance, clearly communicating tradeoffs and risk Qualifications You'll have... Bachelor’s degree in Computer Science, Electrical/Computer Engineering, Systems Engineering (or equivalent experience). 7+ years engineering experience in complex systems, including deep experience in network performance modeling/analysis. Demonstrated ability to build and apply models to predict/explain latency, jitter, utilization, and coupling in multi-node networks. Real hands-on knowledge of Ethernet, CAN/CAN-FD, and LIN in a vehicle context (constraints, failure modes, integration realities). Strong software engineering skills (Python, C++, or similar) used for analysis automatio