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

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What you’ll work on

Full posting
  • Identify and develop patentable design improvements for automotive spare parts

  • Support invention disclosures, prior-art analysis and patent filings

  • Develop predictive models for spare part health, anomaly detection and failure prediction

  • Analyze service records, warranty claims, telematics and sensor data for patterns

  • Evaluate components for design, CAE, manufacturability and serviceability

From the employer’s posting
Identify and develop patentable design improvements for automotive spare parts.
Support invention disclosure, prior-art analysis, and patent filing activities.
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.
Evaluate automotive components from design, CAE, manufacturability, and serviceability perspectives.
Apply at Mercedes-Benz Group

Posting record

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Status in our records
Live
First seen by us
Sep 22, 202652 days ago
Recorded sightings
249
Last seen by us
Nov 14, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 52

Similar jobs usually come down between day 8 and day 76.

At Mercedes-Benz Group, jobs usually come down by about day 28.

From 5,460 similar postings that came down, and 79 of Mercedes-Benz Group’s. Coming down is not always a hire.

Mercedes-Benz Group is hiring

17 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down quickly
Hiring record

See how this role fits your experience

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  • Python
  • SQL
Where the posting names them
- 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

Your next step

Complete your application on jobs.mercedes-benz.com. The employer’s form will show what is required.

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Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 612, the most 1,081, and the latest week had 1,068.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

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
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Location & working pattern

Bangalore, Indien

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