• Architect end-to-end ML and synthetic data pipelines to drive continuous improvement in virtual manufacturing
• Develop advanced generative and optimization models for scheduling, material flow, quality prediction, and process control
• Evaluate and implement modern optimization algorithms
• Lead model validation using industrial analytics metrics
• Establish standards for data/model lifecycle management

Requirements

Typically requires a Bachelor’s degree, preferably in computer science, Artificial Intelligence, Data Science, mathematics, or a similar field with quantitative coursework
7-10 years of professional experience in associated field is required
Master’s degree and 4-6 years of experience, or a PhD and 1-3 years of experience in relevant field
Deep expertise in machine learning and deep learning techniques
Demonstrated experience in leveraging classical optimization techniques
Advanced Python knowledge for high-performance analytical workloads
Deep knowledge of manufacturing process analytics

🔍 ATS Optimization Keywords
Below are skills and terms extracted directly from this job posting to improve Applicant Tracking System (ATS) visibility. This unique feature helps candidates tailor their applications more effectively — a feature exclusive to JobTailor job listings.

Hard Skills

machine learning
deep learning
optimization algorithms
Python
generative models
scheduling models
material flow models
quality prediction models
process control models
industrial analytics metrics

Soft Skills

leadership
communication
organizational skills

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