ML Ops Scientist — Production Optimization & Scheduling

The Judge Group; Muskegon Charter Township (MI); On-site; USD 150,000 - 170,000; Full time

Job summary

The Judge Group is seeking a Machine Learning Operations Scientist/Production to drive optimization models and deploy them in manufacturing settings. The role emphasizes ILP/MILP modeling, constraint programming, and solver technologies, with Python-based development across data preparation, model construction, and solver integration.

Applicants should hold a graduate degree (MS or PhD) in operations research and bring strong ML fundamentals, digital twin experience, and scheduling expertise.

Qualifications

• MS or PhD in operations research required.
• Demonstrated expertise in ILP/MILP modeling, constraint programming, and solver technologies (Gurobi, CPLEX, OR Tools, Pyomo, PuLP).
• Working knowledge of machine learning, feature engineering, and model evaluation.
• Experience with digital twin development and simulation modeling.
• Experience in operations research, optimization modeling, or production scheduling.
• Hands-on experience implementing optimization models in Python, including data preparation, model construction, and solver integration.
• Ability to independently design, test, and validate new mathematical formulations.
• Experience applying OR techniques to manufacturing, supply chain, or industrial systems.
• Experience developing large scale scheduling models (job shop, flow shop, batching, resource constrained scheduling).
• Familiarity with stochastic optimization, robust optimization, or reinforcement learning for decision making.
• Strong statistical background and experience analyzing industrial/manufacturing data.

Skills

ILP/MILP modeling

Constraint programming

Machine learning basics

Data analysis

Scheduling optimization

Stochastic optimization awareness

Education

MS or PhD in operations research

Tools

Gurobi

CPLEX

OR Tools

Pyomo

PuLP

Job description

The Judge Group is seeking a Machine Learning Operations Scientist/Production to drive optimization models and deploy them in manufacturing settings. The role emphasizes ILP/MILP modeling, constraint programming, and solver technologies, with Python-based development across data preparation, model construction, and solver integration.

Applicants should hold a graduate degree (MS or PhD) in operations research and bring strong ML fundamentals, digital twin experience, and scheduling expertise.