- Deployment. Support that methods and tools developed in the group impact the Carrier business through engagement in global product projects, including capture and formulation of computational problems arising in such projects
- Methods, tools and algorithms. Ensure that appropriate computational methods, tools and algorithms for large-scale numerical optimization are based on sound mathematical foundations and are deployed to match the needs of the Carrier business, including contributing to the architecture, development, testing and documentation of the methods and tools developed in the group
- Modeling for optimization. Support development of mathematical models for thermo-fluid systems are built based on principles and best practices that secure reliable application of numerical optimization algorithms
- Talent. Support development and training of staff within Carrier product teams and within the Computational Engineering group; contribute to talent pipeline by supervising student internships and theses
- Master's Degree in an Engineering Discipline
- 5+ years of experience with modeling and optimization in industrial applications
- PhD preferred
- Proven ability to capture engineering design and operation problems as mathematical programming problems (NLPs), including attention to reliable convergence of such problems
- Proficient with the mathematical theory (applied mathematics, numerical analysis and functional analysis), algorithmic foundations (notably existence and convergence proofs), and methods/tools for numerical optimization (SQP, interior point method, etc.) of large-scale systems
- Experience from using common algorithms/solvers for large-scale gradient-based non-linear programs, e.g., IPOPT, CONOPT, KNITRO, and WORHP, including their respective applicability to different types of problems. Knowledge about discrete optimization formulations, methods, and algorithms is a merit
- Familiarity with physics-based modeling principles and best practices of thermo-fluid systems, such as vapor compression cycles or power plants
- Familiarity and experience with development of computational platforms and tools in Python or equivalent
- Familiarity with using HPC and cloud-based platforms for computation at scale.
- Demonstrated ability to work as part of a multidisciplinary team and an entrepreneurial attitude towards technological innovation in a global environment
- Self-starter who is well-organized in an international team environment, with proven communication skills
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Staff Systems Engineer - Kennesaw, United States - Carrier
Description
About the role
As a Senior Optimization Engineer you provide technical expertise in the area of numerical optimization of thermo-fluid systems which are core to the Carrier business – this includes trade-off and optimize energy efficiency, production cost and operating economy.
You engage with global product teams to solicit business needs and convert those into computational decision-making workflows, methods and tools to radically impact how Carrier products are designed, deployed and operated. Key targets include improving engineering effectiveness as well as developing disruptive, innovative methods for model-based design and operation of Carrier systems.
Looking for that Senior Optimization Engineering professional with deep knowledge and highly developed technical expertise in the theory and practice of model-based optimization. Trains less experienced employees, deploy innovative product solutions to our business, and creates common work practices. You also take active part in product development to support design engineers in adopting and using new methods and tools.
You also work closely with other teams in Systems & Controls COE, including teams responsible for model development (to drive the development of optimization-friendly thermo-fluid models) and controls engineering (to promote the use of computational optimization strategies (MPC, RTO) as needed).
Key Responsibilities:
Required Qualifications:
Preferred Qualifications:
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RSRCAR
Carrier is An Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class.
