R&D Engineer: Modeling

3 days ago

Malden, United States Infinite Cooling Full time

About the Role

Infinite Cooling’s mission is to mitigate water scarcity and reduce emissions around the world by making industrial cooling more efficient. Industrial cooling systems are the largest users of water after agriculture and major users of energy. We help industrial plants reduce their water consumption and energy usage by optimizing the operation of their cooling systems. We are a vibrant startup based in the Boston area, and we are on a mission to be a global leader in cooling for industrial applications. Infinite Cooling is venture-backed and has raised over $16M of capital and was awarded over $3M of prizes and grants.


We are looking for a sharp, tenacious, and creative Modeling Engineer to join our team and lead modeling efforts for Infinite Cooling’s products. Strong communication, flexibility, and the desire to “wear many hats” will all be essential skills.


What you will do

  • Numerically model and analyze the performance of cooling towers and industrial processes in various configurations
  • Use machine learning and/or physics-based approaches to analyze sensor data and develop performance prediction, component diagnostic, and process optimization models
  • Perform data mining and statistical analyses on historical sensor data sets to identify new and relevant data features and assess existing model performance
  • Generate ideas, evaluate proof-of-concept algorithms, and mature new product features
  • Become a subject matter expert in our platform and the underlying models and provide technical support to the rest of the team
  • Lead team discussions on requirements definition for new features and system-level validation testing
  • Collaborate with R&D, software, and electrical engineers to translate models into deployed product features


Requirements

  • MS or equivalent in Engineering or Physics; Ph.D is desired.
  • Professional experience in addition to academic background preferred
  • Demonstrated track record of applying machine learning and/or big data techniques to physics problems
  • Strong knowledge in at least one of thermodynamics, heat transfer, or fluid mechanics
  • Strong programming skills in Python and typical numerical and machine learning packages.
  • Ability to pare down complex problems into achievable steps and complete difficult assignments in a timely manner
  • Strong organizational skills; outstanding written and oral communication required


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