Machine Learning Engineer

What you'll do

• Develop optimization models for factory and supply chain metrics, including capacity, yield, cycle times, costs, throughput, and scheduling.
• Build and maintain digital-twin simulations of assembly lines to identify bottlenecks and test capacity scenarios.
• Integrate operational data sources to generate actionable manufacturing insights.

What they ask for

• Master’s degree or PhD in Operations Research, Industrial Engineering, Management Science, Applied Mathematics, or a related field.
• Proficiency with solvers and modeling languages such as Gurobi, CPLEX, CP-SAT, Pyomo, and GAMS.
• Hands-on experience with simulation platforms such as Arena, FlexSim, SimPy, and AnyLogic.
• Experience with machine learning platforms such as PyTorch and Scikit-learn; excellent communication and presentation skills.

Nice to have

• Experience building GenAI applications with agents and agentic workflows; LLM and LMM development and fine-tuning.
• Familiarity with distributed computing, cloud infrastructure, and orchestration tools such as Kubernetes, Apache Airflow (DAG), Docker, Conductor, and Ray.

Pay

$150,400 and $277,600 (base salary)

Tools

Gurobi, CPLEX, CP-SAT, Pyomo, GAMS, Arena, FlexSim, SimPy

AI focus

Applies machine learning to manufacturing analytics; preferred work includes GenAI applications with agents and agentic workflows, and LLM/LMM development and fine-tuning.