Engineer

TEKsystems

10d•$30 - $40•Onsite

About The Position

Position: Engineer Key Focus Areas: Advanced machine vision theory and classifier development Programming and data automation (image + defect data) Statistical validation of inspection performance PLC / MES / database integration for inspection data Operational SQM system ownership, operator training, and daily troubleshooting are already strong within the team; this role complements rather than duplicates those strengths. Core Responsibilities: Advanced Vision Engineering & Classifier Development Design, train, and optimize defect classifiers beyond basic thresholding Apply image processing fundamentals (filters, morphology, feature extraction) Develop structured training and validation datasets Measure and improve classifier performance using confusion matrices, ROC curves, and error metrics Reduce false positives while maintaining customer‑critical defect sensitivity Data Analysis, Automation & Programming Develop Python, MATLAB, or similar scripts for offline image and defect analysis Automate defect trend analysis, reporting, and performance monitoring Query and manage defect data using SQL or database tools Build repeatable workflows that extend beyond built‑in SQM software tools System Integration & Controls Collaboration Interface SQM systems with PLCs, MES, SCADA, and quality databases Support alarm logic design and data handshaking with production systems Collaborate with controls, IT, and automation teams on architecture and reliability Improve end‑to‑end data flow from inspection to actionable insights Statistical Validation & Quality Analytics Apply SPC, capability analysis, and formal statistical methods to inspection data Quantify inspection effectiveness and justify parameter changes scientifically Support root cause investigations with statistically grounded evidence Cross‑Functional Engineering Support Partner with process and metallurgical engineers to translate defect data into process improvements Support corrective actions, yield improvement, and scrap reduction initiatives Provide technical mentorship and knowledge transfer within the SQM team Schedule: Primarily Mon–Fri, with occasional off‑shift support Environment: Industrial manufacturing, frequent production floor interaction

Requirements

Advanced machine vision theory and classifier development
Programming and data automation (image + defect data)
Statistical validation of inspection performance
PLC / MES / database integration for inspection data

Responsibilities

Design, train, and optimize defect classifiers beyond basic thresholding
Apply image processing fundamentals (filters, morphology, feature extraction)
Develop structured training and validation datasets
Measure and improve classifier performance using confusion matrices, ROC curves, and error metrics
Reduce false positives while maintaining customer‑critical defect sensitivity
Develop Python, MATLAB, or similar scripts for offline image and defect analysis
Automate defect trend analysis, reporting, and performance monitoring
Query and manage defect data using SQL or database tools
Build repeatable workflows that extend beyond built‑in SQM software tools
Interface SQM systems with PLCs, MES, SCADA, and quality databases
Support alarm logic design and data handshaking with production systems
Collaborate with controls, IT, and automation teams on architecture and reliability
Improve end‑to‑end data flow from inspection to actionable insights
Apply SPC, capability analysis, and formal statistical methods to inspection data
Quantify inspection effectiveness and justify parameter changes scientifically
Support root cause investigations with statistically grounded evidence
Partner with process and metallurgical engineers to translate defect data into process improvements
Support corrective actions, yield improvement, and scrap reduction initiatives
Provide technical mentorship and knowledge transfer within the SQM team