Machine Learning Operations Scientist/Production

The Judge Group, INC.; Muskegon (MI); On-site; USD 90,000 - 130,000; Full time

Job summary

The Judge Group, INC. seeks a Machine Learning Operations Scientist/Production to advance optimization-driven decisions. The role emphasizes ILP/MILP modeling, simulation, and integration of solver technologies within production systems.

Qualified candidates have graduate OR training, hands-on Python optimization, and experience applying OR techniques to manufacturing and scheduling scenarios. A strong statistical background is a plus for data-driven evaluation.

Qualifications

• MS or PhD with specialization in operations research.
• Strong background in ILP/MILP and constraint programming is required.
• Experience with solver technologies (Gurobi, CPLEX, OR Tools, Pyomo, PuLP).
• Working knowledge of machine learning, feature engineering, and model evaluation.
• Experience with digital twins and simulation modeling is preferred.
• Expertise in OR applications to manufacturing, scheduling, or production systems.

Skills

ILP/MILP modeling

Constraint programming

Solver technologies

Machine learning

Feature engineering

Model evaluation

Digital twin development

Operations research scheduling

Python optimization

Stochastic/Robust/RL methods

Statistical analysis

Education

Graduate degree in OR (MS/PhD)

Tools

Gurobi

CPLEX

OR-Tools

Pyomo

PuLP

Job description

Our client is currently seeking a Machine Learning Operations Scientist/Production

• Graduate degree (MS or PhD) with specialization in operations research.
• 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.
• Demonstrated experience in digital twin development and simulation modeling
• Demonstrated 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.