{"schemaVersion":"jobsearcher.job.v1","id":"d16a17c4f6fb5906176d3bb6","url":"https://jobsearcher.com/jobs/d16a17c4f6fb5906176d3bb6","canonicalUrl":"https://jobsearcher.com/jobs/d16a17c4f6fb5906176d3bb6","title":"Senior Optimization Engineer","description":"Job Description\nSeeking 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.\n\nKey Responsibilities\n\nDevelop and apply multi-objective optimization methods for engineering problems involving tradeoffs among performance, cost, mass, durability, efficiency, or other attributes\n\nBuild, validate, and improve optimization models for simulation-driven and data-driven engineering applications\n\nFormulate engineering problems as mathematical optimization models, including objectives, constraints, and decision variables\n\nUse and integrate commercial optimization tools and solvers as well as custom-developed optimization codes\n\nWork with cross-functional engineering teams to translate real-world design challenges into robust optimization workflows\n\nAnalyze Pareto-optimal solutions and provide engineering insights to support decision-making\n\nSupport model calibration, sensitivity studies, design space exploration, and surrogate/model-reduction approaches where appropriate\n\nDocument methods, assumptions, and results, and communicate findings clearly to technical and non-technical stakeholders\n\nRequired Qualifications\n\nMaster's or Ph.D. in Mechanical Engineering, Aerospace Engineering, Industrial Engineering, Applied Mathematics, Operations Research, Computer Science, or a related field\n\nStrong experience applying multi-objective optimization to engineering problems\n\nExperience in optimization model development\n\nExperience using commercial optimization software, solvers, or frameworks\n\nStrong understanding of mathematical optimization techniques such as gradient-based optimization, nonlinear programming, evolutionary algorithms, surrogate-based optimization, or mixed-integer optimization\n\nExperience working with simulation-based engineering tools and computational models\n\nStrong programming and problem-solving skills\n\nPreferred Qualifications\n\nPh.D. with demonstrated research in engineering optimization or related fields\n\nExperience with commercial optimization codes such as CPLEX, Gurobi, modeFRONTIER, HEEDS, LS-OPT, iSight, GT-SUITE optimizer, or similar tools\n\nExperience with surrogate modeling, reduced-order modeling, or multi-fidelity optimization\n\nExperience in automotive, CAE, crashworthiness, thermal, structural, manufacturing, or multidisciplinary engineering optimization, simulation software such as LS-DYNA, ABAQUS.\n\nAbility to work in a collaborative environment and influence technical direction across teams\n\nDesired Technical Skills\n\nMulti-objective optimization and Pareto tradeoff analysis\n\nEngineering model formulation and simulation-based optimization\n\nCommercial and custom optimization code development\n\nNumerical methods, statistics, and design of experiments\n\nPython, MATLAB, C++, or similar technical computing languages\n\nFamiliarity with finite element, multiphysics, or system-level engineering models\n\n#J-18808-Ljbffr","company":"Optimal Cae","rawCompany":"optimal cae","city":"Brooklyn","state":"NY","isRemote":false,"isActive":false,"createdAt":"2026-06-28T03:52:51.068Z","occupations":[{"code":"17-2199.00","title":"Engineers, All Other","slug":"engineers-all-other"},{"code":"15-2031.00","title":"Operations Research Analysts","slug":"operations-research-analysts"},{"code":"17-2141.00","title":"Mechanical Engineers","slug":"mechanical-engineers"}],"industries":[{"code":"541715","title":"Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)","slug":"research-and-development-in-the-physical-engineering-and-life-sciences-except-nanotechnology-and-biotechnology"},{"code":"541330","title":"Engineering Services","slug":"engineering-services"},{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Senior Optimization Engineer","description":"Job Description\nSeeking 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.\n\nKey Responsibilities\n\nDevelop and apply multi-objective optimization methods for engineering problems involving tradeoffs among performance, cost, mass, durability, efficiency, or other attributes\n\nBuild, validate, and improve optimization models for simulation-driven and data-driven engineering applications\n\nFormulate engineering problems as mathematical optimization models, including objectives, constraints, and decision variables\n\nUse and integrate commercial optimization tools and solvers as well as custom-developed optimization codes\n\nWork with cross-functional engineering teams to translate real-world design challenges into robust optimization workflows\n\nAnalyze Pareto-optimal solutions and provide engineering insights to support decision-making\n\nSupport model calibration, sensitivity studies, design space exploration, and surrogate/model-reduction approaches where appropriate\n\nDocument methods, assumptions, and results, and communicate findings clearly to technical and non-technical stakeholders\n\nRequired Qualifications\n\nMaster's or Ph.D. in Mechanical Engineering, Aerospace Engineering, Industrial Engineering, Applied Mathematics, Operations Research, Computer Science, or a related field\n\nStrong experience applying multi-objective optimization to engineering problems\n\nExperience in optimization model development\n\nExperience using commercial optimization software, solvers, or frameworks\n\nStrong understanding of mathematical optimization techniques such as gradient-based optimization, nonlinear programming, evolutionary algorithms, surrogate-based optimization, or mixed-integer optimization\n\nExperience working with simulation-based engineering tools and computational models\n\nStrong programming and problem-solving skills\n\nPreferred Qualifications\n\nPh.D. with demonstrated research in engineering optimization or related fields\n\nExperience with commercial optimization codes such as CPLEX, Gurobi, modeFRONTIER, HEEDS, LS-OPT, iSight, GT-SUITE optimizer, or similar tools\n\nExperience with surrogate modeling, reduced-order modeling, or multi-fidelity optimization\n\nExperience in automotive, CAE, crashworthiness, thermal, structural, manufacturing, or multidisciplinary engineering optimization, simulation software such as LS-DYNA, ABAQUS.\n\nAbility to work in a collaborative environment and influence technical direction across teams\n\nDesired Technical Skills\n\nMulti-objective optimization and Pareto tradeoff analysis\n\nEngineering model formulation and simulation-based optimization\n\nCommercial and custom optimization code development\n\nNumerical methods, statistics, and design of experiments\n\nPython, MATLAB, C++, or similar technical computing languages\n\nFamiliarity with finite element, multiphysics, or system-level engineering models\n\n#J-18808-Ljbffr","datePosted":"2026-06-28T03:52:51.068Z","dateModified":"2026-06-28T03:52:51.068Z","hiringOrganization":{"@type":"Organization","name":"Optimal Cae","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Brooklyn","addressRegion":"NY","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"d16a17c4f6fb5906176d3bb6"},"url":"https://jobsearcher.com/jobs/d16a17c4f6fb5906176d3bb6"}}