Principal Optimization Engineer

Arods Industrivag 32, 422 43 Hisings Backa

求人ID 30209803 職種 Engineering

Posted Start Date July 6, 2026

応募する

Join Carrier’s Computational Engineering team within the Systems & Controls Center of Excellence and help shape the future of HVAC innovation.

We develop advanced model-based methods, optimization algorithms, and ML-enabled tools that power smarter product design, improved system performance, and efficient real-world operation. Our work directly impacts global products by turning complex engineering challenges into scalable, data-driven solutions.

You’ll collaborate with international product teams, research institutions, and cross-functional experts to bring cutting-edge optimization and control strategies into real-world applications.

Your key responsibilities will be the following

•Design and deploy optimization methods and tools for thermo-fluid systems (chillers, heat pumps, hydronic systems)

• Translate business and engineering needs into mathematical models and decision-making workflows

• Develop and implement optimization-based control strategies (e.g., MPC, real-time optimization)

•Partner with global product teams to embed advanced tools into product development and operation

•Ensure robust, scalable approaches using non-linear and mixed-integer optimization techniques

• Drive adoption of ML/surrogate models in optimization workflows

•Collaborate across modeling, controls, and platform teams to deliver end-to-end solutions

•Mentor engineers, support training initiatives, and contribute to technology roadmap development

Who we're looking for

Required

• Master’s degree in Engineering, Applied Mathematics, or related field

•Extensive experience in model-based engineering, optimization, or computational methods

Preferred

• PhD in Mechanical, Control, Applied Math, Engineering Physics, or Chemical Engineering

•Considerable experience in numerical optimization (NLP, MILP) and solver tools (e.g., IPOPT, KNITRO)

•Deep understanding of optimization theory, numerical methods, and algorithm design

•Experience with thermo-fluid systems modeling (HVAC, vapor compression, energy systems)

•Experience with real-time optimization and control systems

•Proficiency in Python (Pyomo preferred) and scalable computing platforms (cloud/HPC)

•Proven ability to lead in multidisciplinary, global environments

What we offer

We offer a variety of flexible working arrangements and development opportunities for you to grow at Carrier. You will receive a competitive salary and additional benefits including the following:

• Company pension scheme

• Company contributed Share Incentive Plan

• Employee Assistance Programme

• You may be eligible for an annual incentive

In addition to compensation you will have the opportunity to

•Work on high-impact, global engineering challenges

•Influence how next-generation HVAC systems are designed and operated worldwide

•Collaborate with top experts across academia and industry

•Drive innovation at the intersection of physics, optimization, and machine learning

Pay Range

The annual salary for this position is between 648,000 and 1,295,000 sek annually Factors which may affect pay within this range include, but are not limited to, skills, education, experience, and other unique qualifications of the successful candidate.     

Other Compensation

This position is entitled to short-term cash incentives, subject to plan requirements.

Equal Treatment and Non-Discrimination

Carrier is committed to equal treatment and non-discrimination principles.  

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, or disability, or any otherapplicable  protectedclass.  

If you require a reasonable accommodation to complete the application process,participatein an interview, or otherwise engage in the hiring process, please contact us at [email protected]. We will make every effort to meet your needsin accordance withapplicable laws. 