Innovation Engineer – Automotive Design, AI & Predictive Analytics (Spare Parts)

Develop patentable innovations and AI/ML-based monitoring solutions for automotive spare parts, integrating automotive engineering, CAD/CAE, data analytics, and IP development.

Lead innovation initiatives via design thinking workshops, patent filing support, and product improvement focusing on reliability, manufacturability, and cost optimization.

Create predictive models for spare part health, failure prediction, and warranty analytics using multiple automotive data sources and collaborate cross-functionally for design validation and aftermarket analytics.

Bachelor's or Master's degree in Automobile Engineering, Mechanical Engineering, Computer Science, AI & Data Science, or related fields.

Experience with automotive systems, CAD/CAE, design for manufacturing, Python, SQL, data analytics, and machine learning fundamentals.

Demonstrated exposure to patent creation and intellectual property processes in automotive context.

Work Experience Required: Not explicitly mentioned in the JD

Experienced in combining physical automotive product engineering with AI-driven digital analytics for aftersales and predictive maintenance solutions.

Capable of managing end-to-end innovation processes including patent disclosures, cross-functional collaboration, and technology exploration.

Skilled in leveraging large automotive datasets for actionable insights and developing robust predictive models in an automotive R&D environment.