Innovation Engineer – Automotive Design, AI & Predictive Analytics (Spare Parts)
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Before you apply
LocationIndia-Karnataka-Bangalore
Company size10,000+ people
First seenOct 18, 2026 · 2w ago
Verified live6d ago
At a glanceSummarised by Seekless from the posting.
B.Tech/M.Tech in Automobile Engineering, Mechanical Engineering, Computer Science, AI & Data Science, or related disciplines
Strong understanding of automotive systems, components, and aftersales processes
Working knowledge of CAD, CAE, and Design for Manufacturing (DFM)
Experience in Python, SQL, data analytics, and machine learning fundamentals
Knowledge of predictive modeling, anomaly detection, and Exploratory Data Analysis
Demonstrated innovation mindset with exposure to patent generation and intellectual property processes
Strong analytical, problem-solving, communication, and stakeholder management skills
Skills
Python
SQL
machine learning
CAD
CAE
Design for Manufacturing (DFM)
Project Exclusivity
Objective
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Develop patentable automotive spare part innovations and AI/ML-based monitoring solutions by combining expertise in automotive engineering, CAD/CAE, manufacturability, data analytics, and intellectual property development.
Scope of Work
Innovation & Patent Development
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Identify and develop patentable design improvements for automotive spare parts.
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Conduct design thinking workshops with R&D and cross-functional teams to generate innovative concepts.
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Support invention disclosure, prior-art analysis, and patent filing activities.
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Drive innovation initiatives focused on product enhancement, reliability, manufacturability, and cost optimization.
Automotive Design & Engineering
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Evaluate automotive components from design, CAE, manufacturability, and serviceability perspectives.
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Perform feasibility assessments and support concept validation activities.
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Collaborate with design, testing, quality, manufacturing, and aftersales teams.
AI/ML & Aftersales Analytics
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Develop predictive models and monitoring algorithms for spare part health, anomaly detection, failure prediction, and warranty analytics.
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Leverage service records, warranty claims, vehicle diagnostics, telematics, sensor data, and parts sales data to identify patterns and trends.
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Support development, validation, and continuous improvement of AI/ML algorithms and monitoring solutions.
Data Analytics & Insights
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Collect, preprocess, and analyze large datasets from multiple automotive data sources.
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Generate actionable insights, KPIs, and performance indicators to support business and engineering decisions.
Research & Technology Exploration
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Investigate emerging technologies in AI, Machine Learning, Generative AI, Predictive Maintenance, and Automotive Aftersales.
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Create proof-of-concepts and assess applicability to future products and services.
Engineer with a proven passion for innovation, automotive product development, patent creation, and AI-driven analytics, capable of bridging physical product engineering with intelligent digital solutions.
Requirements
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B.Tech/M.Tech in Automobile Engineering, Mechanical Engineering, Computer Science, AI & Data Science, or related disciplines.
•
Strong understanding of automotive systems, components, and aftersales processes.
•
Working knowledge of CAD, CAE, and Design for Manufacturing (DFM).
•
Experience in Python, SQL, data analytics, and machine learning fundamentals.
•
Knowledge of predictive modeling, anomaly detection, and Exploratory Data Analysis
•
Demonstrated innovation mindset with exposure to patent generation and intellectual property processes.
•
Strong analytical, problem-solving, communication, and stakeholder management skills