Simulation Engineer
Inherent Technologies
Simulation Engineer
Key Responsibilities
Model Development: Develop complex simulation models using SimPy, AnyLogic, or FlexSim to represent real-world operational processes (e.g., warehousing, logistics networks, manufacturing lines) per the design and specifications from Google SME's
Scenario Analysis: Execute comprehensive "what-if" analyses to test changes in layout, staffing, logic, or equipment before physical implementation as per the provided specifications.
Data Integration: Collaborate with SME's to clean and prepare input data, defining statistical distributions (Poisson, Gaussian, etc.) that accurately reflect process variability.
Optimization: Apply Operations Research techniques (mixed integer programming, heuristics, scheduling, graph optimization and queueing theory) within simulation environments to identify global optima versus local improvements.
Verification: Conduct rigorous testing to ensure model behavior matches historical data and reality.
Required Qualifications
Educational Background: BS or MS in Operations Research, Industrial Engineering, Systems Engineering, Computer Science, or a related quantitative field.
Simulation Expertise:
Deep understanding of Discrete Event Simulation (DES) principles (entities, resources, queues, events).
Proven experience with Agent-Based Simulation (ABS) for modeling decentralized, autonomous behaviors.
Technical Stack:
SimPy: Strong proficiency in Python-based simulation modeling; ability to write custom classes and generators.
Commercial Tools: Hands-on experience with AnyLogic (Java-based scripting) or FlexSim (FlexScript/SQL).
Operations Research: Solid foundation in queueing theory, stochastic processes, and mathematical optimization.
Programming: Integration of version control, automated testing/verification and code review practice. Proficiency in Python (pandas, NumPy, SciPy), Java for model building, data engineering and analysis.
Preferred Qualifications
Advanced querying with SQL for data extraction.
Demonstrated ability to solve complex problems through custom algorithm development.
Strong aptitude for breaking down advanced technical requirements into efficient code in Python
Knowledge of Java (specifically for advanced AnyLogic customization).
Experience integrating simulation models with AI/Reinforcement Learning
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