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What to Expect
As a Tesla Manufacturing Engineer, you have the important role of designing
“The Machine that builds the Machine”. You will work with the cross-functional
teams (Design, Quality, Production, Sustaining, and Supply Chain) throughout
the entire lifecycle of a product (from initial design through prototype
development and into full production) to develop high quality and efficient
manufacturing equipment and processes that will produce the power electronics
that drive our cars and energy products.
What You'll Do
Conduct exploratory studies and analysis to identify assembly processes to
meet product requirements
Identify critical process parameters and quality attributes, and conduct
experiments using Design of Experiments (DOE) methods to determine
sensitivity and acceptable process windows
Develop cause and effect analysis, Process Failure Mode Effects Analysis
(PFMEA) and control plan
Troubleshoot and Identify corrective measures to critical equipment
(mechanical, electrical, thermal, optical etc.) related problems
Conduct Install/qualification of tools including Measurement Systems
Analysis (MCA), Gauge Repeatability and Reproducibility (GRR), Process
Stability and Capability (CP/CPK), and equipment/process matching
Enable Statistical Process Control (SPC), and create standard operation
and maintenance procedures to support the transition to sustainable
production
Execute data driven root cause analysis as part of reject validation and
excursion investigations
Drive continuous improvement & optimization activities to meet production
targets including availability, quality, and performance
What You'll Bring
2+ years of experience developing and deploying assembly (e.g. fastening,
dispense, pick and place, soldering, etc.) and/or test (e.g. electrical,
optical inspection, etc.) processes through high-volume manufacturing
Experience developing and taking new automated manufacturing processes and
equipment from the prototype stage through high volume production
Familiarity with, and interest in grappling with large data sets to drive
decision making
Strong working knowledge of Statistical Analysis, Design of Experiments
(DOE), Gauge Repeatability and Reproducibility (GRR), Failure Mode
Effects Analysis (FMEA), Statistical Process Control (SPC) and other
Six Sigma Tools
Clear understanding of manufacturing production metrics, field data, and
quality and reliability data
Hands-on skills with diagnostics software, hardware, tools, instruments,
general electromechanical systems and measurement techniques
BS/MS/PhD in Chemical/Material/Electrical/Industrial/Mechanical
Engineering, or equivalent experience
