Career Area:
Engineering
Job Description:
JOB PURPOSE: To serve as an experienced individual contributor on projects and assignments that are large and complex in nature and that support and enhance Caterpillar processes and product performance, durability, reliability, quality and serviceability.
JOB DUTIES: Will develop and deliver physics, statistics, and ML-based analytics models of machines, engines, subsystems, and components to support condition monitoring for customers, and to improve product development for enterprise. Will use engineering systems modeling, optimization, advanced statistics and statistical learning techniques including machine learning and deep learning on time-series machine sensor data and other datasets to better understand data patterns, identify device health anomalies, predict equipment failure modes and develop analytics algorithms that deliver customer value on complex IoT systems. Will frame complex technical problems, identify/create/explore alternatives, and formulate/negotiate/develop/validate solutions, and convert concepts to reality.
BACKGROUND/EXPERIENCE:
Required Qualifications:
- Masters Degree or foreign equivalent in Computer Science, Mechanical Engineering or Materials Science or related area.
- 2 years of relevant industry experience in applying gradient-based and heuristic optimization tools and methods to solve complex problems in product development of earthmoving machines. Relevant industry experience must include conducting topology optimization, fatigue analysis, design of experiment, surrogate modeling techniques, sensitivity analysis, and reliability analysis. Experience must also include: (i) computer programming in C++ and Java, (ii) mathematical programming in Matlab and Python, and (iii) using structural and multidisciplinary optimization software such as Optistruct, iSIGHT or similar software.
Alternatively, will accept a Bachelor Degree or foreign equivalent in Computer Science, Information Technology or related area and 5 years of relevant industry experience in applying gradient based and heuristic optimization tools and methods to solve complex problems in product development of earthmoving machines. Relevant industry experience must include conducting topology optimization, fatigue analysis, design of experiment, surrogate modeling techniques, sensitivity analysis, and reliability analysis. Experience must also include: (i) computer programming in C++ and Java, (ii) mathematical programming in Matlab and Python, and (iii) using structural and multidisciplinary optimization software such as Optistruct, iSIGHT or similar software.
EEO/AA Employer. All qualified individuals - Including minorities, females, veterans and individuals with disabilities - are encouraged to apply.
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