Senior Optimization Engineer

Job Description

Seeking a highly motivated engineer or scientist with strong expertise in multi-objective optimization applied to complex engineering problems. This role will focus on developing, implementing, and deploying optimization methods to support engineering design, analysis, and decision-making across multidisciplinary applications.

• Develop and apply multi-objective optimization methods for engineering problems involving tradeoffs among performance, cost, mass, durability, efficiency, or other attributes
• Build, validate, and improve optimization models for simulation-driven and data-driven engineering applications
• Formulate engineering problems as mathematical optimization models, including objectives, constraints, and decision variables
• Use and integrate commercial optimization tools and solvers as well as custom-developed optimization codes
• Work with cross-functional engineering teams to translate real-world design challenges into robust optimization workflows
• Analyze Pareto-optimal solutions and provide engineering insights to support decision-making
• Support model calibration, sensitivity studies, design space exploration, and surrogate/model-reduction approaches where appropriate
• Document methods, assumptions, and results, and communicate findings clearly to technical and non-technical stakeholders

• Master's or Ph.D. in Mechanical Engineering, Aerospace Engineering, Industrial Engineering, Applied Mathematics, Operations Research, Computer Science, or a related field
• Strong experience applying multi-objective optimization to engineering problems
• Experience in optimization model development
• Experience using commercial optimization software, solvers, or frameworks
• Strong understanding of mathematical optimization techniques such as gradient-based optimization, nonlinear programming, evolutionary algorithms, surrogate-based optimization, or mixed-integer optimization
• Experience working with simulation-based engineering tools and computational models
• Strong programming and problem-solving skills

• Ph.D. with demonstrated research in engineering optimization or related fields
• Experience with commercial optimization codes such as CPLEX, Gurobi, modeFRONTIER, HEEDS, LS-OPT, iSight, GT-SUITE optimizer, or similar tools
• Experience with surrogate modeling, reduced-order modeling, or multi-fidelity optimization
• Experience in automotive, CAE, crash worthiness, thermal, structural, manufacturing, or multidisciplinary engineering optimization, simulation software such as LS-DYNA, ABAQUS.
• Ability to work in a collaborative environment and influence technical direction across teams

• Multi-objective optimization and Pareto tradeoff analysis
• Engineering model formulation and simulation-based optimization
• Commercial and custom optimization code development
• Numerical methods, statistics, and design of experiments
• Python, MATLAB, C++, or similar technical computing languages
• Familiarity with finite element, multiphysics, or system-level engineering models