System Integration Engineer

Vehicle Systems Integration Engineer, Diagnostics

experience-6 8 Year

Foster city, CA onsite

Fulltime / contract

Systems Integration Engineer, Diagnostics The Vehicle System Integration develops requirements for the hardware systems, power distribution, network topologies, and diagnostic capabilities that enable a world-class autonomous vehicle architecture. As a Diagnostics Engineer , you will own the design, development, and validation of diagnostic algorithms for the vehicle- centric systems, ensuring robust fault detection across all operating conditions. This role demands deep expertise in control theory, and strong skills in developing production-quality C++ software. You will work at the intersection of hardware, firmware, and autonomy software to deliver diagnostics that keep our fleet safe and serviceable at scale. You will collaborate closely with cross-functional teams in Vehicle System Engineering, Systems Design & Mission Assurance, Firmware, Fleet Operations, and Vehicle Program Management to translate system-level requirements into real-time onboard diagnostic monitors.

Key Responsibilities

● Diagnostic Algorithm Design & Implementation: Architect and implement real-time diagnostic monitors in modern C++, including signal-level plausibility checks, degradation detection, and fault isolation logic. Perform software unit testing, HIL testing, and automated regression tests to validate diagnostic algorithms prior to final implementation

● Diagnostic Requirement Engineering: Author formal diagnostic monitor requirements (detection thresholds, debounce strategies, fault response actions) traceable to system-level or component level failure modes; verify requirements against fleet and bench data.

● Data-Driven Analysis & Validation: Leverage large-scale fleet data in Databricks to characterize faults, tune detection thresholds, validate algorithm performance (detection rate, false-positive rate), and drive continuous improvement.

● Fault Troubleshooting & Root Cause Analysis: Lead investigation of field-reported faults using telemetry, logged data, and replay tools; identify root causes spanning hardware, firmware, calibration, and environmental factors.

● Documentation & Knowledge Transfer: Produce clear technical specifications, design documents, and service procedures that enable Fleet Operations technicians to diagnose and resolve faults efficiently.

● Continuous Improvement: Monitor fleet-wide diagnostic KPIs; propose and implement algorithm refinements, new monitors, and process improvements.

Qualifications

● Education: Bachelor's degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, Robotics, Aerospace Engineering, or a related technical field. Master's degree preferred

● Experience: .6–8 years of professional experience in diagnostics, embedded controls, or vehicle systems engineering within the automotive, autonomous vehicle, aerospace, or robotics industry. Required Skills

● C++ Proficiency: Strong, demonstrable C++ development skills in production or safety-critical environments;

● Control & Estimation Theory: Hands-on experience designing and implementing control algorithms, state estimators, or model-based diagnostic observers

. ● Vehicle Diagnostics Expertise: Working knowledge of diagnostic standards and protocols (UDS / ISO 14229, DTC management, OBD-II / SAE J1979) and communication buses (CAN, LIN, Automotive Ethernet).

● Data Analysis: Proficiency with Python for data analysis and visualization; experience working with large-scale telemetry datasets (Databricks, or equivalent).

● Problem Solving: Proven ability to systematically decompose complex, multi-domain problems and drive them to root cause under ambiguity.

● Communication: Excellent written and verbal communication skills; able to present technical analyses and recommendations to both engineering peers and non-technical stakeholders.

Preferred Skills

● Experience with functional safety standards (ISO 26262) and FMEA / FTA methodologies.

● Familiarity with model-based development tools (MATLAB/Simulink) for algorithm prototyping and code generation.

● Experience with HIL/SIL testing frameworks for diagnostic validation.