Modeling & Simulation Machine Learning Engineer

This role involves applying machine learning and simulation techniques to optimize manufacturing processes and develop digital twins for consumer goods production. You will work with engineering teams to analyze data and create models that improve product quality and efficiency.

Summarised by InternDoor from Procter & Gamble’s posting, in our own words. The posting itself is the source of truth, so check it before you apply.

• Develop digital twins for virtual manufacturing and optimize production processes
• Use Python, R, and ML tools to create surrogate models for complex engineering systems
• Collaborate with cross-functional R&D teams on real-world manufacturing challenges

Required

• Master’s or PhD master’s or PhD degree in an engineering discipline
• Engineering background Strong foundation in any branch of Engineering (Mechanical, Chemical, Material Science, Electrical, Metallurgical, Aerospace etc)
• Coding experience Hands on coding experience and mastery in one or more languages (Python, R, C++)
• Knowledge in Python or R knowledge in either Python or R is required
• AI-assisted tools Experience using AI-assisted software development tools, such as GitHub Copilot, to develop, test, and document engineering applications
• Big data analysis Demonstrated expertise in analysis of large data sets (“big data”) to deliver actionable insights from data
• Surrogate models Demonstrated expertise in combining first principles concepts/science in any field of engineering with advanced ML approaches to develop surrogate models
• Real world problems Prior experience and/or strong interest in “real world” problems. This includes knowledge of manufacturing processes and data infrastructure
• Communication skills Strong communication skills. The candidate is the link between “incomprehensible” data and engineers who need to act on new insights

Nice to have

• Integrated Control Systems Interest or experience in Integrated Control Systems
• ML, Deep Learning ML, including Deep Learning
• Engineering background with ML Engineering background with ML specialization &/or research publications
• Data Mining Data Mining (such as data preparation, regression, classification tools, SVM)
• Optimization Optimization (global, local, stochastic methods)
• Model Reduction Model Reduction, Dimensionality Reduction
• Data bases and data processing
• Analytical Tools/Applications Unix/Linux, Scientific Computing: R, Python, C++, Java, Scala, Deep Learning frameworks: Keras, TensorFlow, High-Performance Parallel and Distributing Computing (CPU and GPU), Data Visualization, Data Management Systems

Read from Procter & Gamble’s posting. Its own wording is the one that counts.

1. Check what they ask for. Read the requirements above.
2. Tailor your resume to the role. Put the work that matches these skills first. InternDoor’s resume tailor does it against this posting.
3. Apply on Procter & Gamble’s careers site. The application is on pgcareers.com, not on InternDoor. We never ask for a fee.

Apply soon: postings like this can close without notice, and this one states no deadline.

Posted

8 Nov 2026, on LinkedIn

First seen by InternDoor

8 Nov 2026, within 8 minutes of being posted

Last checked

8 Nov 2026: the application page loaded. That shows the page is up, not that Procter & Gamble is still filling the role.

Application deadline

Procter & Gamble has not stated one

Leaves InternDoor

By 8 Dec 2026, our 30-day limit for LinkedIn listings, or sooner if the application closes

Application page

pgcareers.com

What we checked, and what the dates mean

The date this listing leaves InternDoor is our own rule, not a deadline set by Procter & Gamble. Postings can close earlier, at any time.

What “last checked” means: our checker opened the application page and it answered. That shows the page is up; it does not prove the role is still being filled, and Procter & Gamble has not confirmed anything to us.

InternDoor has recorded 5 engineering postings from Procter & Gamble in India since Jul 2026.

When this listing comes down, this address says the role has closed and lists open roles like it, instead of a dead end.

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