System Product Design Engineer

Austin, TX, US • Posted 14 hours ago • Updated 1 hour ago
Full Time
On-site
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Innovation
  • Test Methods
  • Consumer Electronics
  • Mathematics
  • Product Design
  • Computer Hardware
  • Quality Assurance
  • Analytics
  • Risk Assessment
  • Collaboration
  • Manufacturing
  • Evaluation
  • Testing
  • Packaging Engineering
  • Physics
  • Mechanics
  • Systems Design
  • Metrology
  • Standard Operating Procedure
  • Technical Writing
  • Test Plans
  • Reporting
  • Failure Analysis
  • Data Analysis
  • Tableau
  • JMP
  • MATLAB
  • Reliability Engineering
  • Machining
  • Data Collection
  • Consumer Goods
  • Market Risk
  • Mechanical Engineering
  • Python
  • Swift
  • Data Acquisition
  • Modeling
  • Performance Metrics
  • Machine Learning (ML)
  • Electromechanics
  • Data Visualization
  • Database

Summary

Imagine what you can do here. Apple is a place where extraordinary people gather to do their lives best work. Together we create products and experiences people once couldn't have imagined, and now, can't imagine living without. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do.

APPLE INC has the following available in Austin, Texas. Develop and validate packaging designs for future products through the development of mechanical, thermal, and customer use test methodologies. Develop quality assurance and critical performance for future designs using math models. Run physical testing of packaging and consumer electronics to ensure performance meets internal cost and performance targets. Correlate math models to physical tests to improve the prediction of future simulations to develop new tools, metrology, and materials. Work cross-functionally with multiple engineering and product design disciplines. Provide guidance for Domestic and International engineering services and contractors to be complementary. Develop hardware and software test guidelines and systems to collect analytics on design performance. Create arrays of measurements and failure analysis metrics to benchmark designs. Work with internal and external teams to refine plans, optimizing value tensions between groups. Build positive relationships with supplier teams while driving them to execute validation plans. Statistically analyze data to provide risk assessments and technical recommendations. Collaborate with project teams reviewing materials, manufacturing processes and evaluation testing standards. International travel required 10%. 40 hours/week.

Bachelor's degree or foreign equivalent in Physics, mechanical engineering, packaging engineering, or related field and 4 years of experience in the job offered or related occupation.\n\n1 year of experience with each of the following skills is required:\n\nUtilizing knowledge of physics to demonstrate a strong foundation of 1st level principles, dynamic and static mechanics, and environmental responses to evaluate system design performance.\nUsing metrology equipment, standard operating procedure technical writing, test planning and reporting to deploy test programs and failure analysis triages.\nUtilizing statistical data analysis using tools and software such as Tableau, JMP, or Matlab to visualize and interpret data, as well as deploy and scale data bases.\nExperience in reliability engineering responsible for sampling, design of experiment scope, and execution to lead design test programs.\nExperience in material analysis working on quantifying material performance impact to design(s) efficacy.\nUtilizing electromechanical automation and machining to customize and integrate optical, mechanical, and thermal data acquisition systems for data collection.\nExperience in consumer goods or commercial engineering systems to generate and evaluate route to market risk analysis.\nTesting analysis to convert qualitative experiences into measurable quantitative mechanical principles.\nUtilizing Python or Swift to build new data acquisition tools, applications, and modeling techniques to measure and collect design performance metrics.\nUtilizing machine learning development and deployment in needs to automate electromechanical test systems, create data visualization tools, or connect to internal databases.

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  • Dice Id: 90733111
  • Position Id: 6cfabc2c0dc48adaeec92c5c91949dc2
  • Posted 14 hours ago
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