Principal Optimization Engineer

About Carrier

Carrier Global Corporation, global leader in intelligent climate and energy solutions, is committed to creating innovations that bring comfort, safety and sustainability to life. Through cutting‑edge advancements in climate solutions such as temperature control, air quality and transportation, we improve lives, empower critical industries and ensure safe transport of food, lifesaving medicines and more. Since inventing modern air conditioning in 1902, we lead with purpose: enhancing the lives we live and the world we share.

We continue to lead because of our world‑class, inclusive workforce that puts the customer at the center of everything we do. For more information, visit  or follow on Carrier social media at @Carrier.

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 physical and data‑driven (ML) modeling for optimization, 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.

The group also develops and maintains computational platforms and tools for deployment to Carrier product teams. Engineers in the group work on global projects in conjunction with Carrier business units and external research organizations (universities and research institutes) to create worldwide business impact through new product and process innovations.

The candidate will provide technical leadership in the area of numerical optimization of thermo‑fluid systems which are core to the Carrier business – including design and deployment of product design methods, sales tools, and supporting the development of optimization‑based supervisory controls. A strong background in physics‑based modeling for optimization of HVAC equipment including chillers, heat pumps and hydronic systems is therefore key.

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 Center of Excellence 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 junior engineers in the group, supervision of student interns, organization of optimization trainings, and technology roadmap development.

• Location: Based full‑time and onsite at the Kennesaw, GA facility located at 1025 Cobb Place Boulevard, 30145.
• Work Flexibility:
  Following the successful completion of the initial onboarding and acclimation period, this position may offer a hybrid option to work remotely up to one or two days per week.

• 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.
• Modeling for optimization. Ensure that models used for system‑level…