Optimization Engineer

Position: Optimization EngineerLocation: Warren, MichiganDuration: 1.5 years – possibility of extensionsCompensation: $35/hr to $45/hrExact compensation may vary based on several factors, including skills, experience, and education. Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.Qualifications:Masters Degree or PhD in Engineering2-3 years of experience with multi-object optimization & applying it to engineering problemsExperience in optimization model development – HEEDS, LS-OPT, iSight, or own developmentExperience programming in python & C++Familiar with FEM – Finite Element MethodsExperience with LS-Dyna or CAE packageDay to Day:Insight Global is looking for an Optimization Engineer in the Warren, Michigan area. The optimization engineer will be responsible for developing, implementing, and deploying optimization methods to support engineering design, analysis, and decision-making across multidisciplinary applications.Additional Responsibilities Include:Develop and apply multi-objective optimization methods for engineering problems involving tradeoffs among performance, cost, mass, durability, efficiency, or other attributesBuild, validate, and improve optimization models for simulation-driven and data-driven engineering applicationsFormulate engineering problems as mathematical optimization models, including objectives, constraints, and decision variablesUse and integrate commercial optimization tools and solvers as well as custom-developed optimization codesWork with cross-functional engineering teams to translate real-world design challenges into robust optimization workflowsAnalyze Pareto-optimal solutions and provide engineering insights to support decision-makingSupport model calibration, sensitivity studies, design space exploration, and surrogate/model-reduction approaches where appropriateDocument methods, assumptions, and results, and communicate findings clearly to technical and non-technical stakeholders