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

Mercedes-Benz Group; Bengaluru; Presencial; INR 900.000 - 1.300.000; Jornada completa

Descripción de la vacante

Mercedes-Benz Group in Bengaluru seeks a technically proficient innovator to bridge automotive product engineering with intelligent digital solutions. The role focuses on patentable spare part innovations, AI/ML monitoring, and data-driven insights across design, engineering, and aftersales domains.

Ideal candidates will demonstrate a strong background in automotive systems, CAD/CAE, and data science, with a track record of collaboration across R&D, manufacturing, and service teams.

Formación

• B.Tech or M.Tech in Automobile/Mechanical Eng, CS, AI & Data Science or related fields.
• Strong knowledge of automotive systems and aftersales processes.
• Proficient in Python, SQL, data analytics and ML fundamentals.
• Experience with predictive modeling, anomaly detection and EDA.
• Innovative mindset with IP exposure and patent processes.

Responsabilidades

• Develop patentable spare part innovations and AI/ML monitoring solutions.
• Identify design improvements and conduct invention disclosures.
• Collaborate with design, testing, quality, manufacturing, and aftersales teams.
• Build predictive models and analytics for spare parts health and warranty data.
• Analyze large automotive datasets to generate actionable insights.
• Explore emerging AI/ML technologies and proof-of-concepts.

Conocimientos

Automotive systems

Python

SQL

Data analytics

Machine learning fundamentals

Exploratory Data Analysis

Educación

B.Tech in Automobile Engineering

M.Tech in Automobile Engineering

B.Tech in Mechanical Engineering

B.Tech in Computer Science

Herramientas

CAD/CAE

DFM

Descripción del empleo

Tasks

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.

Qualifications

• 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