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Optimization Engineer

CarrierCarrier·HVAC and Refrigeration

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About the role

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Carrier Global Corporation, global leader in intelligent climate and energy solutions is committed to creating solutions that matter for people and our planet for generations to come. From the beginning, we've led in inventing new technologies and entirely new industries. Today, we continue to lead because we have a world-class, diverse workforce that puts the customer at the center of everything we do.

About the role

  • The candidate will apply advanced numerical optimization of thermo-fluid systems which are core to the Carrier business – including design and deployment of product design methods, sales tools, and on-line supervisory controls.
  • The candidate will 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. The candidate will take active part in product development to support design engineers in adopting and using new methods and tools. The candidate will 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). In addition, the candidate will contribute to mentoring of junior engineers in the group, supervision of student interns, organization of optimization trainings, and technology roadmap development.

Key Responsibilities:

As a Optimization Engineer, you’ll be responsible for:

  • Deployment. Ensure 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 that relate to “supervisory” control formulations, trade studies and implementation. Use control theoretic tools for robustness and stability guarantees in addition to performance optimality.

  • Methods, tools and algorithms. Ensure that appropriate computational methods, tools and algorithms for designing dynamic, optimal supervisory control are based on sound mathematical foundations and are deployed to match the needs of the Carrier business.

  • Provide technical expertise in areas of system engineering, including but not limited to mathematical programming (NLP, MILP, MINLP, Meta-heuristics), uncertainty quantification, sensitivity analysis, stochastic programming, data analysis, gradient-based optimization algorithms, scientific computing, machine learning, AI methodologies.

  • Modeling for dynamic supervisory control based on optimization formulations. 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 for control applications.

  • Participation in global multidisciplinary projects, ensuring on-time and high-quality project execution and delivery.

  • Explore, develop and leverage emerging computational engineering, optimization or control technologies and tools, based on business needs and capability development needs in the organization.

  • 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

Requirements

As a minimum you must have:

  • Master’s Degree in Engineering or Sciences (e.g. HVACR, Control, Chemical, Thermal Energy, Mechanical, Fluid, Aerospace, Industrial, Operational Research, Applied Mathematics, etc.)

  • 5+ years of engineering role or an advanced degree with a minimum of 3+ years in engineering field with a strong element of model-based computation and optimization 

  • In-depth knowledge and experience in optimization and mathematical programming theories, algorithms, methods, tools of complex and large systems problem solving

  • Proven expertise and working experience of nonlinear programming optimization algorithms (e.g. SQP, Interior point method, etc.), including attention to reliable convergence of such problems.

  • Direct deployment experience with online real-time optimization closed-loop control is highly favored

  • Experience of developing and implementing algorithms in solving ODE, PDE, DAE systems

  • Experience with development of computational platforms and tools in Python or equivalent.

  • Understanding of fundamental principles in fluid mechanics, HVAC systems, and heat transfer, thermodynamics along with foundational product-domain knowledge.

  • Fluent English (both written and spoken) and excellent communication skills.

 

Preferred Qualifications:

Although not necessary, it would be nice if you have:

  • PhD is preferred

  • Proven ability to capture engineering design and operation problems as mathematical programming problems (MILPs, GDPs, MINLPs), including attention to decomposition large and complex problems. (e.g. Benders, column generation)

  • Working experience with design on-line closed loop supervisory controllers (e.g., MPC/NMPC), including stability and robustness analysis and deployment to relevant industrial processes.

  • In-depth knowledge and experience with 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, algorithms and solvers is a merit e.g. CPLEX, GUROBI Knowledge of metaheuristics and implementation experience is a plus (e.g, GA, PSO, ACO, etc.)

  • Expertise and working experience with physics-based modeling principles such as heat transfer and thermodynamics and best practices of thermo-fluid systems, such as vapor compression cycles or power plants. Familiarity with HVAC product domain knowledge is a plus

  • Expertise in object-oriented programming language (Python, Julia, C, C++, C#, Java, etc.), simulation/optimization platform (Pyomo, Dakota, Dymola, Matlab/Simulink, AMPL, GAMS, gPROMS, ALAMO, etc.), or optimization solver (IPOPT, SNOPT, CONOPT, CBC, CPLEX, Gurobi, BARON, NOMAD, etc.).

  • Knowledge of virtual power plant, energy storage system, electric grid is a plus

  • Familiarity with robust design, VMEA, stochastic programing, uncertainty quantification

  • Familiarity with machine learning techniques, including supervised and unsupervised learning (e.g., gradient boosting, MLP, KNN, PCA, Gaussian processes) and reinforcement learning, with application experience in predictive modeling of system performance.

  • Familiarity with using HPC and cloud-based platforms for computation at scale.

  • Demonstrated ability to lead and 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, and has excellent interpersonal, leadership and communication skills.

Benefits

We are committed to offering competitive benefits programs for all of our employees, and enhancing our programs when necessary.

Our commitment to you

Our greatest assets are the expertise, creativity and passion of our employees. We strive to provide a great place to work that attracts, develops and retains the best talent, promotes employee engagement, fosters teamwork and ultimately drives innovation for the benefit of our customers. We strive to create an environment where you feel that you belong, with diversity and inclusion as the engine to growth and innovation. We develop and deploy best-in-class programs and practices, providing enriching career opportunities, listening to employee feedback and always challenging ourselves to do better. This is The Carrier Way.

Join us and make a difference.

Apply Now!

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.

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Aplyr's read

Carrier is a global leader in HVAC and refrigeration, attracting professionals in engineering, environmental health, and safety, with a focus on innovation and sustainability.

Synthesized from recent postings & public sources

What's promising

  • Carrier's strong global presence ensures diverse career opportunities across multiple regions.
  • The company invests in technological innovation, enhancing its product offerings and market competitiveness.
  • Carrier's commitment to sustainability aligns with growing environmental concerns and industry trends.

What to watch

  • The HVAC industry faces cyclical demand, impacting job stability during economic downturns.
  • Carrier's large organizational structure may slow decision-making processes.
  • Intense competition in the HVAC sector could pressure profit margins and growth.

Why Carrier

  • Carrier pioneered modern air conditioning, establishing a legacy of innovation.
  • The company offers comprehensive solutions, integrating HVAC, refrigeration, and fire and security systems.
  • Carrier's focus on sustainability is evident in its energy-efficient product lines and corporate practices.

Aplyr’s read is generated by AI from public sources. Was it useful?

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About Carrier

Carrier is a global leader in heating, ventilation, air conditioning, refrigeration, and fire and security solutions.

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