Optimization Engineer
Listed on 2026-07-08
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Engineering
AI Engineer (Applied/Software), Software Engineer, Process Engineer, Systems Engineer
Duration
: 1.5 years – possibility of extensions
Compensation
: $35/hr to $45/hr
Exact 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 Engineering
- 2-3 years of experience with multi-objective optimization & applying it to engineering problems
- Experience in optimization model development – HEEDS, LS-OPT, iSight, or own development
- Experience programming in Python & C
- Familiar with FEM – Finite Element Methods
- Experience with LS-Dyna or CAE package
Overview:
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.
- 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.
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