Senior Engineer, Automotive Prognostics and Health Management (PHM)

Role Description:

• As a Prognostics and Health Management (PHM) Senior Engineer on the Fleet Health Management (FHM) team, you will develop advanced PHM solutions that eliminate unplanned downtime, optimize maintenance strategies, and drive system-wide improvements across the fleet. You will own the design, deployment, and performance monitoring of health models for Software-Defined Vehicles (SDVs), working closely with cross-functional teams to integrate PHM strategies into vehicle platforms and service operations.


• This role offers the opportunity to lead technical initiatives, apply reliability principles combined with data-driven methodologies, and shape the future of health management capabilities that improve vehicle reliability, availability, and customer satisfaction.

Responsibilities: 

• Technical Leadership & Strategy: Develop scalable, robust health management solutions across vehicle platforms, influencing design and serviceability from early-stage concept to deployment.


• Cross-functional Collaboration: Collaborate with engineering, software, data science, service, and operations teams to embed PHM features into vehicle systems and digital infrastructure.


• Advanced Health Model Development: Develop, validate, and deploy advanced fault detection, diagnostic, and prognostic algorithms using statistical and machine learning methods, ensuring scalability, efficiency, and reliability of the models.


• Maintenance Intelligence & Optimization: Drive the development of health assessment tools and maintenance prioritization frameworks that improve uptime and optimize service resource planning.


• Model Performance Monitoring & Continuous Improvement: Establish monitoring pipelines and metrics to assess health model performance post-deployment and identify opportunities for refinement.


• FHM Platform and Framework Evolution: Guide PHM system integration, leveraging inputs from FMEA/FMEDA, diagnostics, and field performance data.


• Innovation and Industry Alignment: Stay at the forefront of PHM technology, Software-Defined Vehicle architectures, and data-driven reliability practices. Apply emerging trends to advance our tools, methodologies, and product capabilities.

Qualifications:

• Bachelor’s or Master’s degree in Electrical, Mechanical Engineering, Computer Science, or related fields.


• 5+ years of experience in PHM, reliability engineering, diagnostics, or related areas.


• Proficiency in Python, SQL, and Git with strong data analysis and statistical modeling skills.


• Hands-on experience with machine learning for predictive maintenance or reliability forecasting.


• Experience developing and deploying ML models in edge or cloud environments.


• Deep understanding of system reliability principles and failure analysis techniques.


• Strong verbal and written communication skills for documenting and reporting to leadership.


• One Team Mentality: Must be a self-starter, capable of independently identifying and pursuing opportunities to advance the team's vision. Must regularly seek and incorporate feedback to ensure alignment with the team’s goal.

Preferred Qualifications:

• Familiarity with automotive standards, vehicle dynamics, and telematics data.


• Exposure to Machine Learning Operations (MLOps) and scalable deployment practices.


• Experience with Bayesian networks or probabilistic modeling.


• Experience with uncertainty quantification techniques, such as Bayesian Inference, Monte Carlo simulation.


• Experience with building Digital Twin using physics-based modeling.


• Knowledge of automotive diagnostics, FMEA/FMEDA methodologies, and embedded system design.


• Experience with C++ and software integration for real-time systems.


• Experience with requirements management tools such as JAMA and Caemo.


• Familiarity with Software-Defined Vehicle architectures and service operations integration.