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

Mercedes-Benz Group AG; Bengaluru; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

Mercedes-Benz Group AG in Bengaluru seeks an engineer passionate about automotive product development, patent creation, and AI-driven analytics to bridge physical engineering with intelligent digital solutions.

You will drive patentable innovations, evaluate CAD/CAE concepts, and develop ML-based monitoring for spare parts, leveraging sensor data, diagnostics, and service records to generate actionable insights for design and aftersales.

Qualifications

• B.Tech/M.Tech in Automobile Engineering, Mechanical Engineering, CS, AI & Data Science, or related fields.
• Strong understanding of automotive systems, components, and aftersales processes.
• Experience with CAD/CAE, and design for manufacturability (DFM).
• Proficient in Python, SQL, data analytics, and ML fundamentals.
• Knowledge of predictive modeling, anomaly detection, and Exploratory Data Analysis.

Responsibilities

• Develop patentable spare-part innovations and AI/ML-based monitoring solutions.
• Lead design thinking workshops with R&D and cross-functional teams to generate innovative concepts.
• Support invention disclosures, prior-art analysis, and patent filing activities.
• Drive innovation initiatives focused on product enhancement, reliability, manufacturability, and cost optimization.
• Collaborate with design, testing, quality, manufacturing, and aftersales teams.

Skills

Python

SQL

Data analytics

Machine learning fundamentals

Exploratory Data Analysis

Education

B.Tech/M.Tech in Automobile Engineering, Mechanical Engineering, Computer Science, AI & Data Science, or related disciplines

Tools

CAD

CAE

DFM

Job description

Aufgaben

Project Exclusivity

Objective

• 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

• Identify and develop patentable design improvements for automotive spare parts.
• Conduct design thinking workshops with R&D and cross-functional teams to generate innovative concepts.
• Support invention disclosure, prior-art analysis, and patent filing activities.
• Drive innovation initiatives focused on product enhancement, reliability, manufacturability, and cost optimization.

Automotive Design & Engineering

• Evaluate automotive components from design, CAE, manufacturability, and serviceability perspectives.
• Perform feasibility assessments and support concept validation activities.
• Collaborate with design, testing, quality, manufacturing, and aftersales teams.

AI/ML & Aftersales Analytics

• Develop predictive models and monitoring algorithms for spare part health, anomaly detection, failure prediction, and warranty analytics.
• Leverage service records, warranty claims, vehicle diagnostics, telematics, sensor data, and parts sales data to identify patterns and trends.
• Support development, validation, and continuous improvement of AI/ML algorithms and monitoring solutions.

Data Analytics & Insights

• Collect, preprocess, and analyze large datasets from multiple automotive data sources.
• Generate actionable insights, KPIs, and performance indicators to support business and engineering decisions.

Research & Technology Exploration

• Investigate emerging technologies in AI, Machine Learning, Generative AI, Predictive Maintenance, and Automotive Aftersales.
• 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.

Qualifikationen

• 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