Job TitleCloud Prognostics Systems Engineer (MBSE | MATLAB/Simulink | C++)
Overview We are seeking an experienced Cloud Prognostics Systems Engineer to design and develop prognostic solutions for connected automotive systems. The ideal candidate will have expertise in Model-Based Systems Engineering (MBSE), MATLAB/Simulink, C++, cloud data analysis, vehicle diagnostics, and systems integration. This role involves collaborating with cross-functional engineering teams to develop scalable, reliable, and data-driven prognostic features throughout the product lifecycle.
Key Responsibilities - Develop prognostic degradation models using MATLAB/Simulink and generate production-quality C++ code.
- Apply Model-Based Systems Engineering (MBSE) methodologies using SysML and MagicDraw.
- Define system boundaries, logical and physical architectures, interface definitions, and functional allocations.
- Design control logic and physical system models while ensuring efficient integration into automotive software platforms.
- Conduct laboratory testing, including dyno testing and data acquisition activities.
- Select, install, calibrate, and validate prototype vehicle sensors.
- Collect, process, and analyze high-fidelity sensor and vehicle telemetry data.
- Perform system safety and cybersecurity assessments, including FMEA, FMEDA, and threat modeling.
- Design systems compliant with ISO 26262 and ISO 21434.
- Develop and optimize network communication and transport strategies for connected vehicle systems.
- Create behavioral scenarios using Gherkin for system interactions.
- Analyze cloud-based telemetry data using SQL and decode vehicle communication data using database translation tables.
- Develop and maintain system requirements using ALM tools such as Jama, Jira, and Teamcenter.
- Ensure end-to-end requirements traceability across software, hardware, and verification activities.
- Integrate prognostic applications with vehicle communication networks, including CAN, LIN, and Automotive Ethernet.
- Apply Robust Engineering principles, including Parameter Diagrams (P-Diagrams), DFMEA, and validation methodologies.
- Analyze engineering metrics and support continuous improvement of feature performance.
- Collaborate with cross-functional engineering teams throughout product development and launch.
Required Qualifications - Master's degree.
- 5+ years of automotive engineering and/or data analytics experience.
- Strong experience with MATLAB/Simulink and C++ development.
- Experience generating C++ code from MATLAB/Simulink models.
- Experience with Model-Based Systems Engineering (MBSE), SysML, and MagicDraw.
- Strong understanding of vehicle architecture, sensors, diagnostics, and prognostics.
- Experience with Robust Engineering principles, including DFMEA, P-Diagrams, requirements definition, and validation.
- Experience with SQL and cloud-based data analysis.
- Knowledge of automotive communication protocols including CAN, LIN, and Automotive Ethernet.
- Experience using Application Lifecycle Management tools such as Jira, Jama, and Teamcenter.
- Strong communication and collaboration skills with cross-functional engineering teams.
Preferred Qualifications - PhD or Master's degree in Automotive Engineering, Systems Engineering, Mechanical Engineering, Electrical Engineering, Electronics Engineering, Computer Science, or a related field.
- 2+ years of experience developing system requirements using Gherkin scenarios.
- Experience performing systems analysis and designing complex systems and subsystems.
- Experience analyzing connected vehicle data or large datasets.
- Experience performing failure analysis, FMEA, and issue resolution during product development.
- Experience designing cloud-to-vehicle communication solutions and optimizing network protocols.
- Experience leading feature development from concept through production.
- Experience leading cross-functional defect investigation and resolution activities.
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