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. About This Role The Computational Engineering group within Systems & Controls COE (Carrier WHQ) develops and deploys model‑based methods and tools for the design and operation of Carrier products. This includes using mathematical models for design decisions, quantification of system uncertainty, and securing efficient field operation. Core technology areas are physical and data‑driven modeling for optimization, large‑scale continuous and discrete optimization, variability analysis, data analytics, machine learning, numerical and algorithm analysis, and understanding requirements for reliable mathematical models. The group also develops and maintains computational platforms and tools for deployment to Carrier product teams. Engineers work on global projects with Carrier business units and external research organizations to create worldwide business impact through new product and process innovations. Position Summary The candidate will provide technical leadership in numerical optimization of thermo‑fluid systems that are core to the Carrier business – designing and deploying product design methods, sales tools, and supporting optimization‑based supervisory controls. A strong background in physics‑based modeling for HVAC equipment optimization (chillers, heat pumps, hydronic systems) is key. The candidate will engage with global product teams to convert business needs into computational decision‑making workflows and will support design engineers in adopting new methods. The role includes mentoring junior engineers, supervising student interns, organizing optimization training, and contributing to technology roadmapping. Location and Work Flexibility Location: Kennesaw, GA – 1025 Cobb Place Boulevard, 30145. Full‑time and onsite. Work Flexibility: After the initial onboarding period, a hybrid option may allow remote work up to one or two days per week. Key Job Responsibilities Deploy methods and tools to the Carrier business through engagement in global product projects, capturing and formulating computational problems for supervisory control, trade studies, and implementation. Ensure models used for system‑level optimization satisfy requirements for efficient optimization, including non‑linear programming and mixed integer/discrete programming. Develop computational methods, tools and algorithms for designing dynamic, optimal supervisory control, grounded in sound mathematical foundations and aligned with business needs. Support development of mathematical models for thermo‑fluid systems based on principles and best practices that enable reliable application of numerical optimization algorithms for control. Apply machine learning and surrogate methods to optimization applications where appropriate. Support talent development and training within Carrier product teams and the Computational Engineering group, including supervising student internships. Required Qualifications Master’s Degree in Engineering or Sciences. 10+ years in an engineering role with a strong element of model‑based computation and optimization. Willing and able to travel domestically and internationally up to 10% of the year. Preferred Qualifications PhD or advanced degree in an Engineering discipline (applied mathematics, mechanical, control, engineering physics, chemical engineering). Proven ability to capture engineering design and operation problems as mathematical programming problems (NLPs and MILPs), ensuring reliable convergence. In‑depth knowledge and experience with mathematical theory (numerical analysis, functional analysis), algorithmic foundations (existence and convergence proofs), and tools for numerical optimization (SQP, interior point methods) of large‑scale systems. Experience with common solvers for large‑scale gradient‑based nonlinear programs (IPOPT, CONOPT, KNITRO, WORHP) and discrete optimization formulations. Expertise in physics‑based modeling principles of thermo‑fluid systems, such as vapor compression cycles or power plants. Experience with designing and deploying real‑time optimization algorithms for estimation and control. Familiarity with computational platforms and tools in Python or equivalent; knowledge of Pyomo is a merit. Familiarity with HPC and cloud‑based platforms for computation at scale. Demonstrated leadership and entrepreneurial attitude in a multidisciplinary, global environment. Self‑starter, well‑organized in an international team setting, with excellent interpersonal, leadership and communication skills. Pay Range The annual salary for this position is between $117,500.00 and $234,500.00. Factors that 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 Short‑term cash incentives, subject to plan requirements. Benefits Health Care Benefits: Medical, Dental, Vision; Wellness incentives. Retirement Benefits. Time off and Leave: Paid vacation days, up to 15 days; paid sick days, up to 5 days; paid personal leave, up to 5 days; paid holidays, up to 13 days; birth and adoption leave; parental leave; family and medical leave; bereavement leave; jury duty leave; military leave; purchased vacation. Disability: Short‑term and long‑term disability. Life Insurance and Accidental Death and Dismemberment. Tax‑Advantaged Accounts: Health Savings Account; Health Care Spending Account; Dependent Care Spending Account. Tuition Assistance. Carrier EEO Statement and Accommodations Process Carrier is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status or any other applicable state or federal protected class. Carrier provides affirmative action in employment for qualified individuals with a disability and protected veterans in compliance with section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. If you require a reasonable accommodation for the application process or interview, please contact View email address on click.appcast.io. Application Deadline Applications will be accepted for at least 3 days from Job Posting Date: 15 June 2026. Job Applicant's Privacy Notice Please click on the link to review the Job Applicant Privacy Notice. Use of AI Technology‑enabled tools may support parts of the recruitment process, with oversight by people. #J-18808-Ljbffr Carrier