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Remote Systems Engineer - Kennesaw, GA, United States - Carrier
Description
At Carrier, you're joining the world leader in healthy, safe,sustainableand intelligent building and cold chain solutions.As an employer of choice, we strive to provide a great place to work that attracts,developsand retains the best talent, promotes employee engagement, fosters teamwork and ultimately drives innovation for the benefit of our customers.
In short, Carrier's greatest assets are the expertise,creativityand passion of our employees- and we're excited for you to join the team.
The Computational Engineering group within Systems & Controls COE (Carrier WHQ) has responsibility for developing and deploying model-based methods and tools for design and operation of Carrier products.
This includes using mathematical models for taking product design decisions, quantification of system uncertainty, and securing efficient operation in the field.
The core technology areas of the group are large-scale continuous and discrete optimization, variability analysis, data analytics, machine learning, numerical and algorithm analysis, as well as understanding requirements for mathematical models to be reliably used by numerical algorithms.
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.
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.
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).
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 projectsEnsure 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
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
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.)
Familiarity and experience with development of computational platforms and tools in Python or equivalentFamiliarity with using HPC and cloud-based platforms for computation at scale.
Self-starter who is well-organized in an international team environment, with proven communication skills
#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.