Modeling & Simulation Machine Learning Engineer

Role overview

What you’ll do

• Use modern data analysis and machine learning with engineering first principles and physical data to understand complex manufacturing systems.
• Develop digital twins and fast surrogate models for engineering process qualification, optimization, and prediction.
• Work with cross-functional R&D scientists and engineers in research, manufacturing processes, and data infrastructure.
• Assess in-house development versus turnkey solutions and own build-or-buy recommendations and technical due diligence.
• Translate insights across raw materials, manufacturing processes, and final products into actionable business recommendations.

Education and experience

• Master’s or PhD in an engineering discipline and demonstrated practical experience and/or publications applying AI/ML with engineering principles to complex problems.
• Advanced degrees in computer science, statistics, applied mathematics, or related quantitative fields may be considered with demonstrated AI/ML application to engineering problems.
• Strong foundation in an engineering field such as mechanical, chemical, materials science, electrical, metallurgical, or aerospace engineering.
• Hands-on coding mastery in one or more languages; Python or R is required.
• Experience using AI-assisted development tools, such as GitHub Copilot, to develop, test, and document engineering applications.

Additional qualifications and preferred areas

• Demonstrated expertise analyzing large datasets and combining engineering first principles with advanced machine learning to develop surrogate models.
• Prior experience or strong interest in real-world problems, including manufacturing processes and data infrastructure.
• Strong communication and listening skills to understand problems, build trust, and explain context and potential solutions.
• Interest or experience in integrated control systems is a plus.
• Preferred areas include deep learning, engineering and ML research, data mining, optimization, model and dimensionality reduction, databases, and data processing.
• Preferred tools and areas include Unix/Linux, scientific computing languages, Keras, TensorFlow, parallel computing on CPU and GPU, data visualization, and data management systems.

Location

• The posting identifies the Hyderabad office in India.

Schedule

• The job is listed as full time.

About P&G