Simulation Engineer

Inherent Technologies; San Jose (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Inherent Technologies seeks a quantitative simulation expert to build and analyze complex models of warehousing, logistics, and manufacturing systems. You will design DES and ABS models, perform scenario analyses, and integrate data to reflect real-world variability.

Strong optimization and verification skills are essential to ensure models align with historical performance. The role emphasizes advanced programming in Python and Java, with hands-on experience in SimPy, AnyLogic, or FlexSim to

Qualifications

• BS or MS in a quantitative field.
• Deep knowledge of DES and ABS.
• Proficiency with Python-based simulation modeling and AnyLogic/FlexSim scripting.

Responsibilities

• Model Development: Develop complex simulation models using SimPy, AnyLogic, or FlexSim to represent real-world operational processes.
• Scenario Analysis: Execute comprehensive what-if analyses to test changes before physical implementation.
• Data Integration: Clean and prepare input data, define statistical distributions reflecting variability.
• Optimization: Apply OR techniques to identify global optima vs local improvements.
• Verification: Conduct rigorous testing to ensure model behavior matches historical data.

Skills

Discrete event simulation

Agent-based simulation

Queueing theory

Python (SimPy)

Java/AnyLogic scripting

Education

BS or MS in Operations Research/Industrial Engineering/Systems Engineering/CS

Tools

SimPy

AnyLogic

FlexSim

Python

Java

Job description

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