Optimization Engineer
Mid-level Full Time
Tasks
- Build computational platforms and tools in Python
- Build mathematical models for thermo-fluid systems
- Capture engineering design and operation problems as mathematical programming problems
- Create and apply numerical optimization algorithms for control applications
- Create import and simulate Functional Mockup Units using FMI standards
- Deploy optimization methods and tools in product projects
- Design and validate MPC and NMPC supervisory controllers
- Develop and deploy physics based models for thermo-fluid systems
- Develop computational methods and algorithms for dynamic optimal supervisory control
- Ensure reliable convergence of optimization problems
- Formulate computational problems for supervisory control
- Perform stability and robustness analysis for controllers
- Simulate and evaluate large scale gradient based non linear programs
- Supervise student internships and support team training
- Use HPC and cloud platforms for large scale computation
- Use control theoretic tools for robustness and stability
Perks/Benefits
- Employee assistance program
- Flexible schedule
- Health insurance
- Leave policy
- Professional development
Skills/Tech-stack
Cloud Computing | Control Theory | FMI | FMI 2.0 | FMI 3.0 | Fluid modeling | Functional Mockup Units | Functional mockup | Gradient-based optimization | High Performance | High-Performance Computing | Integer linear programming | Interior Point Method | Linear Programming | MPC | Mixed Integer | Mixed-Integer Linear Programming | Model-Predictive Control | NMPC | Nonlinear Programming | Numerical Optimization | Performance Computing | Predictive control | Python | Quadratic Programming | Robustness Analysis | Sequential Quadratic Programming | Stability analysis | Thermo-fluid modeling | Vapor Compression Cycles | Vapor compression
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Regions
Countries
States
Cities
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