System integration Engineer(Diagnostics)

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

Experience:.6 8 years of professional experience in diagnostics, embedded

controls, or vehicle systems engineering within the automotive, autonomous

vehicle, aerospace, or robotics industry.

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.

Experience with implementing prognostics or vehicle health monitoring

Experience with HIL/SIL testing frameworks for diagnostic validation.