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Internship Mathematical Optimization Jobs in Georgia

Machine Learning Intern

Atlanta, GA · On-site

$27 - $42/hr

... an internship: Anomaly detection using deep neural networks Numerical optimization applied to ... Mathematics Natural or Social Sciences Relevant additional backgrounds also considered Essential ...

Machine Learning Intern

Atlanta, GA · On-site

$27 - $42/hr

... an internship: Anomaly detection using deep neural networks Numerical optimization applied to ... Mathematics Natural or Social Sciences Relevant additional backgrounds also considered Essential ...

$110K - $132K/yr

• Contribute to the design, build, deployment, and optimization of AI/GenAI/Agentic AI solutions ... Math, or related field. • Strong Python programming skills (experience with libraries such as ...

Agentic AI Engineer

Atlanta, GA · On-site

$110K - $132K/yr

• Contribute to the design, build, deployment, and optimization of AI/GenAI/Agentic AI solutions ... Math, or related field. • Strong Python programming skills (experience with libraries such as ...

Your insights will be instrumental in optimizing marketing spend, identifying new opportunities ... Strong internships will be considered as relevant experience. * Technical Skills: Advanced ...

Internship Mathematical Optimization information

What is an internship in mathematical optimization?

An Internship in Mathematical Optimization is a temporary position for students or recent graduates to gain practical experience applying mathematical techniques to solve optimization problems. These internships typically involve tasks such as modeling real-world scenarios, developing algorithms, and using software tools to find optimal solutions in areas like logistics, finance, or engineering. Interns often work with experienced professionals, contributing to research projects or business applications while building their technical skills. The role usually requires a solid foundation in mathematics, programming, and analytical thinking.

What types of projects can I expect to work on during an internship in mathematical optimization?

As an intern in Mathematical Optimization, you will typically work on real-world problems that involve designing, implementing, and testing optimization algorithms. Projects may include tasks such as modeling supply chain logistics, scheduling operations, or improving resource allocation for various industries. You'll likely collaborate with data scientists, engineers, and other interns to collect data, build models, and present findings. This hands-on experience helps you develop both technical and teamwork skills, and often includes mentorship from senior optimization experts.

What are the key skills and qualifications needed to thrive in an internship in mathematical optimization?

To thrive in an Internship in Mathematical Optimization, you need a solid background in mathematics, particularly in optimization theory, linear algebra, and programming, usually supported by ongoing or completed studies in applied mathematics, engineering, or a related field. Familiarity with optimization software (like Gurobi or CPLEX), programming languages such as Python or MATLAB, and experience with relevant libraries or frameworks is highly valued. Strong analytical thinking, attention to detail, and effective communication skills help interns stand out when solving complex problems and collaborating with teams. These skills are crucial for developing efficient optimization solutions and contributing meaningfully to research or industry projects.

What is the difference between Internship Mathematical Optimization vs Data Analyst Intern?

AspectInternship Mathematical OptimizationData Analyst Intern
Required CredentialsBasic knowledge of optimization, programming skillsStatistics, data analysis, programming
Work EnvironmentResearch, algorithm development, modelingData collection, reporting, visualization
Industry UsageOperations research, logistics, supply chainBusiness, marketing, finance

Internship Mathematical Optimization focuses on developing and applying algorithms to optimize processes, often in logistics or operations research. Data Analyst Interns analyze and interpret data to support business decisions. While both roles involve data and programming, optimization internships emphasize mathematical modeling, whereas data analysis internships focus on data interpretation and visualization.

What are the most commonly searched types of Mathematical Optimization jobs in Georgia?

The most popular types of Mathematical Optimization jobs in Georgia are:

What are popular job titles related to Internship Mathematical Optimization jobs in Georgia?

For Internship Mathematical Optimization jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Internship Mathematical Optimization jobs in Georgia look for?

The top searched job categories for Internship Mathematical Optimization jobs in Georgia are:

What cities in Georgia are hiring for Internship Mathematical Optimization jobs?

Cities in Georgia with the most Internship Mathematical Optimization job openings:

Principal Optimization Engineer

Carrier Global Corporation

Kennesaw, GA • On-site

$117.50 - $234.50/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 15 days ago


Job description

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 corporate.carrier.com or follow on Carrier social media at @Carrier.

About this role

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.

Position Summary

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.
Key Job Responsibilities
  • 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 optimization for integrated and distributed HVAC energy systems fulfill the requirements for efficient optimization, including non‑linear programming and mixed integer/discrete programming respectively.
  • 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.
  • Modeling for dynamic supervisory control based on optimization formulations. Support development of mathematical models for thermo‑fluid systems that are built based on principles and best practices that secure reliable application of numerical optimization algorithms for control applications.
  • Ensure that appropriate machine learning and surrogate methods applicable to optimization are used in applications.
  • 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 and these.
Required Qualifications
  • Master’s Degree in Engineering or Sciences
  • 10+ years in 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
  • Degree in an Engineering discipline (applied mathematics, mechanical, control, engineering physics, or chemical engineering).
  • Proven ability to capture engineering design and operation problems as mathematical programming problems (NLPs and MILPs), including attention to reliable convergence of such problems.
  • 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, and algorithms is a merit.
  • Expertise and experience with physics‑based modeling principles and best practices of thermo‑fluid systems, such as vapor compression cycles or power plants.
  • Experience with designing and deploying real‑time optimization algorithms with application to estimation and control.
  • Familiarity and experience with development of computational platforms and tools in Python or equivalent. Expertise with Pyomo is a merit.
  • 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.
Pay Range

The annual salary for this position is between $117,500.00 – $234,500.00 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.

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

To learn more about our benefits offering, please click here Work with us | Carrier Corporate. The specific benefits available to any employee may vary depending on state and local laws and eligibility factors, such as date of hire and the applicability of collective bargaining agreements.

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 Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act.

If you require a reasonable accommodation to complete the application process, participate in an interview, or otherwise engage in the hiring process, please contact us at Carrier.Recruiting@carrier.com. We will make every effort to meet your needs in accordance with applicable laws.

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.

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