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Eli Lilly is seeking a Computational Modeling Engineer to develop and deploy discrete event simulation and optimization models across its global manufacturing network. Based in Hyderabad at Lilly's Manufacturing & Quality Technical Hub, this role is part of the Digital Manufacturing Engineering (DME) team within the Corporate Engineering Tech Center (ETC).
You will provide deep modeling expertise to drive decisions for designing new manufacturing systems and improving existing ones. The focus is on discrete manufacturing operations including parenteral fill/finish, device assembly, packaging, and material handling. Key responsibilities include:
• Develop and deploy discrete event simulation and optimization models to increase manufacturing capacity, resilience, compliance, and inspection readiness
• Create capacity, throughput, line-balancing, and bottleneck-analysis models for parenteral and device operations
• Develop Digital Twin computational models of discrete manufacturing lines and logistics networks to provide online modeling capabilities to manufacturing facilities
• Deliver sound interpretation of modeling results by maintaining deep knowledge of queueing theory, stochastic processes, scheduling theory, and numerical methods
• Validate model-based solutions against site operating data through empirical testing and shop-floor investigation
• Prepare technical reports documenting work and contributing to the body of knowledge; publish and present work externally when appropriate
• Foster adoption of discrete simulation and optimization tools across the organization through instruction, consultation, and advocacy
• Identify and implement modeling advances by staying current with external developments in discrete event simulation and optimization
• Develop collaborations with external partners and internal data leads to support discrete manufacturing models and Digital Twin solutions
This is a global role supporting all Lilly Manufacturing sites worldwide. The work directly impacts patients in more than 110 countries.
REQUIREMENTS:
• PhD with 4–8 years of experience OR MS degree with 8–15 years of experience in Industrial Engineering, Operations Research, Chemical Engineering, Mechanical Engineering, or related field
• Minimum 4 years of related work experience (graduate research included)
• Experience developing models in one or more of: discrete event simulation, nonlinear programming, mixed-integer linear programming, or dynamic simulation of discrete systems
• Demonstrated working knowledge of queueing theory, stochastic processes, and numerical/optimization methods
• Strong technical writing and presentation skills
• Capability to solve complex issues with minimal supervision
PREFERRED QUALIFICATIONS:
• Experience with capacity analysis, line balancing, scheduling, and logistics optimization in manufacturing
• Experience with commercial software tools such as ExtendSim®, Frontline Solver®, aspenONE®, or equivalent discrete event simulation platforms
• Experience with statistical analysis and data/model fitting using JMP® or similar tools
• Experience developing digital twins of discrete manufacturing lines
• Experience working with validated systems and in GMP/pharmaceutical industry environments
• Ability to work across different cultures and global manufacturing sites
