PHM Algorithm Engineer

2 weeks ago

Greater Bengaluru Area, India IntelliPredikt Technologies Full time

Company Description (

IntelliPredikt Technologies is a technology focused data-driven organization, with a vision and passion to provide Prognostics solutions for the Connected world. With our state of art Embedded and Platform solutions, we are enabling Scalable Intelligent Prognostics Systems for Connected Vehicles and Machines. 


IntelliPredikt leadership team brings in World Class Product & Service experience with Intelligent Analytics, Intelligent Automation, Embedded Software Systems and Hardware System Engineering to drive innovation and end-to-end cutting-edge AI/ML IoT solutions.


Role Description

The Algorithm Development Engineer will contribute to a modular library of algorithms and models that will be deployed as part of IntelliPredikt’s PHM Library / Platform for a wide variety of customers in the manufacturing industries. The Algorithm Development Engineer needs to be comfortable with engaging in the end-to-end process which includes all steps from data collection to analytics results.

Job Responsibilities

  • Developing physics models of industrial equipment(eg:CNC machines,robots,valves,pumps ) typically found in process/manufacturing industries.
  • Developing algorithms for online fault detection, diagnostics, and prognostics.
  • Validating models and algorithms with a variety of data sources, including simulated data, experimental data and customer data.
  • Directing experimental lab tests, including defining test plans, determining data collection requirements, post- processing data and reporting results.
  • Documenting technical information and communicating it to R&D team members, sales, marketing, management and external stakeholders.
  • Support defining and delivering customer solutions, including instrumentation requirements, algorithm specifications, technical proposals, etc.
  • Work in close collaboration with the software and hardware engineering teams, ensuring that algorithms are appropriately deployed in production environment.
  • Collaboration with a diverse set of individuals including modeling scientists, data scientists, software and hardware engineers, sales engineers, plant operators, and manufacturing industry executives.
  • Supporting market research in various process/discrete industries and adjacent market verticals.
  • 


Required experience:

  • M.tech. or Ph.D. in an engineering field (mechanical or CSE engineering preferred, Ph.D. preferred). At least 3 years of experience in one or more of the following:
  • Predictive maintenance or condition monitoring algorithm development for the process/manufacturing industries (oil and gas, chemical, wastewater, cnc machines, robots etc.).
  • Mechanical System modeling and optimization.
  • Computational physics (CFD/FEA/Multiphysics) applied to industrial equipment, such as electromechanical systems , battery based systems
  • Programming experience in Python, Matlab, or similar scientific computing language.
  • Familiarity with production software development tools and concepts, including:
  • CI/CD pipelines
  • Functional and unit tests
  • Source control systems
  • Object-oriented design
  • Integrated development environments
  • Debugging tools
  • Applied knowledge of data science methods including exploratory data analysis, statistics, feature extraction, data visualization, etc.

Preferred experience and skills:

  • Experience implementing production machine learning models.
  • Familiarity with industry standards for process control equipment, maintenance, reliability, and monitoring, such as API, ASME, ANSI, ISA, etc.
  • Familiarity with model-based reasoning, particularly model-based prognostics.
  • Experience with process or design failure modes and effects analysis (FMEA).
  • Experience reading process and instrumentation diagrams, process flow diagrams, and similar.
  • Intellectual curiosity, as evidenced by a demonstrated ability and willingness to learn new technologies.
  • Strong oral and written communication skills as evidenced by the research output of a graduate-level scholar. 

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