Junior Digital Manufacturing Engineer

We are looking for a Digital Manufacturing Engineer to support manufacturing systems modeling, simulation, optimization, and data-driven operational improvement. The role will work closely with operations, engineering, and technology stakeholders to develop digital models, evaluate manufacturing scenarios, and translate analytical findings into practical business recommendations.

Key Responsibilities

• Support the development, validation, and maintenance of digital models of manufacturing plants, production processes, equipment, labor, and material movement.
• Use Discrete-Event Simulation (DES) and optimization techniques to evaluate throughput, capacity, scheduling, bottlenecks, staffing, and resource utilization.
• Prepare and integrate data from MES, IoT devices, PLCs, production systems, enterprise platforms, and structured files for simulation and analysis.
• Run what-if scenarios and translate simulation results into practical operational recommendations.
• Document model assumptions, data requirements, limitations, validation methods, data lineage, and model readiness criteria.
• Collaborate with plant operations, engineering, and technology stakeholders to validate inputs, review results, and prioritize use cases.
• Create dashboards, visualizations, and concise decision-support materials for business and operational leaders.
• Document model logic, operating procedures, validation methods, and model update requirements.
• Develop repeatable modeling and analytics approaches that can be scaled across multiple manufacturing facilities.
• Stay updated on Digital Manufacturing, Industry 4.0, simulation, optimization, and Smart Factory practices.

Required Qualifications

• Bachelor's degree in Industrial Engineering, Manufacturing Engineering, Mechanical Engineering, Operations Research, Data Science, or a related field.
• 13 years of experience, including internships or academic projects, in manufacturing systems modeling, process simulation, capacity planning, or operational optimization.
• Exposure to Discrete-Event Simulation tools such as AnyLogic, Simio, Tecnomatix Plant Simulation, Arena, or equivalent.
• Foundational knowledge of capacity planning, scheduling, process analysis, and optimization techniques.
• Working knowledge of Python, SQL, or similar tools for data analysis and model integration.
• Strong analytical, problem-solving, documentation, visualization, and stakeholder communication skills.

Preferred Qualifications

• Experience with MES, IoT/PLC data, cloud platforms, and enterprise data integration.
• Exposure to Linear Programming, Mixed-Integer Optimization, heuristics, Machine Learning, or predictive analytics applied to manufacturing.
• Experience deploying models, simulations, or analytics in a cloud or enterprise environment.
• Experience with Power BI, ThoughtSpot, or comparable visualization platforms.

Key Skills

Digital Manufacturing | Manufacturing Simulation | Discrete-Event Simulation | AnyLogic | Simio | Tecnomatix Plant Simulation | Arena | Process Modeling | Capacity Planning | Production Optimization | Scheduling | Python | SQL | MES | IoT | PLC | Industry 4.0 | Smart Factory | Operations Research | Power BI | Data Analytics