Systems Engineer Controls

Company introduction Our client is a leading automotive manufacturer developing advanced prognostic systems for vehicle diagnostics and predictive maintenance. Role summary / purpose Cloud Prognostics Engineer – Systems Engineer responsible for designing and implementing end-to-end prognostic systems using Model-Based Systems Engineering (MBSE) methodologies, cloud integration, and automotive safety standards. Key responsibilities • Define system boundaries, establish logical and physical architectures, map interface definitions, and allocate prognostic functions across physical components (local sensors, central gateways, cloud) • Design control logic using MATLAB and Simulink, model physical system dynamics, and auto-generate production-grade C code • Operate dynamic laboratory environments including dyno testing and data acquisition systems; select, place, and calibrate physical sensors on prototype vehicles • Perform safety and security assessments including FMEA, FMEDA, and cybersecurity threat modeling; ensure compliance with ISO 26262 and ISO 21434 • Design optimized network communication and transport protocols; model behavioral scenarios using Gherkin and implement dynamic data-triggering strategies • Perform SQL analysis on cloud platforms to partition, decode, and analyze raw CAN bus and sensor telemetry data • Elicit, document, and trace complex multi-disciplinary requirements using Application Lifecycle Management tools • Integrate prognostic software applications onto central gateway modules; manage signal routing and resolve network timing conflicts • Apply Robust Engineering principles including Parameter Diagrams to identify system inputs, outputs, error states, and noise factors • Connect technical engineering metrics to real-world quality indicators such as Net Promoter Score and vehicle repair rates • Collaborate cross-functionally to integrate prognostic alerts into user-friendly applications Requirements – education & experience • Master's degree with 5 years of automotive experience in engineering and/or data analytics • 5 years of proven knowledge of Robust Engineering Fundamentals including defining requirements, DFMEA, P-Diagrams, and validation • Knowledge of vehicle architecture and sensors for diagnostics and prognostics feature development • Experience working with system modeling language (MagicDraw) and process/interface mapping • Experience working with Atlassian JIRA, JAMA, and Team Center applications • Ability to clearly communicate technical ideas and findings to cross-functional engineering teams Required skills • MBSE methodologies and tools (SysML, MagicDraw) • MATLAB and Simulink for control logic design and code generation • Automotive communication protocols (CAN, LIN, Automotive Ethernet) • Safety and security standards (ISO 26262, ISO 21434, FMEA, FMEDA) • SQL and cloud platform data analysis • Robust Engineering principles and Parameter Diagrams • Application Lifecycle Management tools (JIRA, JAMA, Team Center) • Vehicle sensor technology and calibration Nice-to-have / preferred skills • PhD or Master's degree in Automotive Engineering, Systems Engineering, Mechanical Engineering, Electrical Engineering, Electronics Engineering, Computer Science, or related field • 2 years of experience defining system requirements using Gherkin scenarios and MATLAB/Simulink for end-to-end feature modeling • 2 years of systems analysis and design experience for systems, subs…