Semtech

Semtech

Senior Quality Process Development Engineer

CAN - Burlington, ON · Senior

Sponsorship not specifiedDetected 28 days ago
PythonAngularSQLMachine LearningData AnalysisData ScienceLLMsStatisticsA/B TestingProcess ImprovementRecruitingElectrical EngineeringMentoring

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Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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About the role

  • This role will define the technical development specifications for quality process improvement activities

Responsibilities

  • Design and build statistical and algorithmic detection tools for wafer probe data - including test hardware integrity checks, software bin/yield outlier detection, parametric drift analysis, and reticle- and wafer-level spatial pattern classification - leveraging Semtech's existing statistical infrastructure (20%)
  • Drive along with the tool software teams the buildup of relationship-analysis and reporting layer that reconciles detection outputs into a consolidated set of distinct issues, including LLM-driven contextualization using product and test/bin naming data, and structured, self-describing output for downstream risk assessment (20%)
  • Identify and drive development and requirements for AI process improvement initiatives among the quality engineering teams. (20%)
  • Partner with Quality Engineering, Product Engineering, and the AI development team to validate system performance against production fab lots, and produce documentation and knowledge-transfer materials that support long-term, in-house ownership of the system (20%)
  • Demonstrated ability to design structured, self-describing system outputs and to write clear technical documentation for engineering audiences

Requirements

  • Proficiency in Python (or equivalent) for data analysis and ML model development, and strong SQL or equivalent skills for working with large structured production datasets
  • Experience with semiconductor test data, wafer probe, or final test engineering, including familiarity with concepts such as software binning, parametric test limits, and wafer map analysis
  • Direct experience with a comparable semiconductor test-data / yield-analysis platform
  • Familiarity with spatial/statistical process control methods (e.g., Tukey-method outlier detection, radial/angular trend analysis, spatial clustering) as applied to manufacturing data
  • Prior experience working in a regulated or quality-critical manufacturing environment where system outputs feed formal disposition or non-conforming material review processes
  • Incumbents may be required to perform job-related tasks other than those specifically included in this description.

Nice to have

  • Master's or PhD preferred
  • Bachelor's degree in Electrical Engineering, Computer Science, Statistics, or a related field required

Compensation

  • A reasonable estimate of the pay range for this position is $95,000CAD-$120,000CAD There are several factors taken into consideration in determining base salary, including but not limited to: job-related qualifications, skills, education an

Benefits

  • 5+ years of professional experience in software engineering, applied statistics, or data science, with a track record of shipping production statistical or machine-learning systems
  • Hands-on experience building and deploying machine learning classification models, including training on labeled data and handling out-of-distribution/novel-category detection

Company info

  • Semtech's Product Quality Engineering team is responsible for the quality and reliability of every wafer that leaves our fabs and OSAT partners on its way to customers.
  • Our engineers thrive on solving complex technical challenges and driving improvements that directly impact product reliability and customer satisfaction including building a new generation of statistical and data-driven tools to detect, characterize, and triage wafer-level quality issues faster and more consistently than manual review alone can achieve.
  • You'll join a team where mentorship, technical excellence, and knowledge sharing create a culture of growth, innovation, and tangible impact.
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