Senior Algorithm Engineer (remote)

About Johnson Controls

At Johnson Controls, we transform the environments where people live, work, learn and play. From optimizing building performance to improving safety and enhancing comfort, we drive the outcomes that matter most. Dedicated to protecting the environment, we deliver our promise in industries such as healthcare, education, data centers and manufacturing. With a global team of 100,000 experts in more than 150 countries and over 130 years of innovation, we are the power behind our customers’ mission.

About Central Utility Plant Optimization

Central plants are the biggest contributor to occupant comfort, the biggest supplier of energy—and the biggest consumer of energy. Building managers can keep it running at optimum efficiency with the next generation of plant optimization software from Johnson Controls. We build on our innovative OpenBlue digital platform to connect systems and data for intelligent, automated decision-making. Our Enterprise Manager Central Utility Plant Optimization (CUPO) solution monitors thousands of variables, gathering data every 15 minutes from your connected equipment and from external sources such as weather forecasts and utility rates. CUPO automatically generates and implements optimization decisions, controlling many brands of equipment and plant types. Customers see rapid ROI, reduced costs, increased reliability, and advancement of sustainability goals.

What you will do

As a member of the OpenBlue AI team, the Senior Algorithm Engineer leads development and maintenance of the numerical algorithms that underpin the CUPO solution. You will improve existing algorithms to cover new equipment types and configurations or enhance optimization performance. The position will also work closely with site and modeling teams to understand reported issues, identify fixes, and resolve bugs in the algorithm code. Finally, you will contribute to development of other autonomous buildings capabilities, including optimization of airside equipment. We prefer to have this individual reside in Eastern time zone, but this is a remote opportunity.

Successful candidates will have a background in engineering and experience debugging software. In particular, candidates should be comfortable reading and understanding code written by others (MATLAB, Python). Expertise in MATLAB is preferred, as is familiarity with chillers, mass/energy balances, and numerical optimization. Experience with Python is also preferred.

How you will do it

· Contribute as a member of the algorithm team with assigned tasks

· Write MATLAB code to implement new CUPO algorithm features

· Review code written by other engineers to improve quality

· Help prioritize and plan tasks in collaboration with product management

· Collaborate with site teams to diagnose and resolve reported issues

· Work independently to identify causes of and plan fixes for bugs

· Develop and maintain test cases to validate algorithm correctness

· Play a direct role in the CUPO evolution, incl. developing Python modules

· Read and write Python code for other autonomous buildings capabilities

· Leverage JIRA to plan work and track open issues

What you will need
Required

· Bachelor's degree in mechanical, electrical, chemical, or other engineering field

· 4+ years of experience in applied engineering

· Familiarity with HVAC equipment (chillers, cooling towers, AHUs, etc.)

· Experience reading, writing, and troubleshooting Matlab code

· Familiarity with Python and standard numeric packages (Numpy, Scipy, etc.)

· Familiarity with optimal-control strategies (e.g., dynamic programming, model-predictive control, reinforcement learning)

Preferred

· Graduate degree related to optimization of building energy systems

· Eight years of experience in applied engineering

· Excellent verbal and written communication skills

· Experience with Python and data-science packages (Pandas, Scikit-Learn, etc.)

· Experience reading and writing C# code

· Experience modeling HVAC equipment (chillers, cooling towers, AHUs, etc.)

· Familiarity with mass and energy balances and thermodynamics

· Familiarity with numerical optimization (e.g., linear/nonlinear programming, mixed-integer linear programming, metaheuristics)

· Proficiency in optimal-control strategies (e.g., dynamic programming, model-predictive control, reinforcement learning)

· Experience writing and debugging numerical simulations

· Experience with JIRA

HIRING SALARY RANGE: $86,000 - $115,000 (Salary to be determined by the education, experience, knowledge, skills, and abilities of the applicant, internal equity, location and alignment with market data.) This role offers a competitive Bonus plan that will take into account individual, group, and corporate performance. This position includes a competitive benefits package. For details, please visit the About Us tab on the Johnson Controls Careers site at