Diagnostics Engineer - Vehicle System Integration

● 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

● 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).

● 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.

● 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 implementing prognostics or vehicle health monitoring

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