Customer Engineer - Data Science / ML DevOps Internship

Applied Materials
Singapore
Workplace: OnsiteInternshipFunction: Data Science & Machine LearningSkills: ["Stakeholder engagement","Process improvement","Data collection","Analysis","Presenting recommendations"]

Work on predictive models that enable a shift from break-fix maintenance to proactive field service. Review the current approach, study model governance needs, and help propose improvements. Collaborate with data scientists and equipment experts to pilot an end-to-end model management framework, along with documentation of best practices. Build practical experience in process improvement, digital transformation, and presenting data-backed recommendations in an operational production environment.

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FursaFursa
Applied Materials
Applied Materials
2 days ago

Customer Engineer - Data Science / ML DevOps Internship

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Source: Company careers pageValidated by: Fursa AI
Last checked: 4 hours agoStatus: Live

Job Summary

Work on predictive models that enable a shift from break-fix maintenance to proactive field service. Review the current approach, study model governance needs, and help propose improvements. Collaborate with data scientists and equipment experts to pilot an end-to-end model management framework, along with documentation of best practices. Build practical experience in process improvement, digital transformation, and presenting data-backed recommendations in an operational production environment.
Location: Singapore
Workplace: Onsite
Employment Type: Internship
Job Function: Data Science & Machine Learning
Seniority: Intern level

Key Responsibilities

  • •Study the existing approach for model governance and propose improvements
  • •Collaborate with data scientists and equipment experts to pilot end-to-end model management
  • •Develop and maintain documentation of best practices for model management
  • •Apply process improvement methodologies and digital transformation in an operational setting
  • •Present data-backed recommendations to stakeholders to support operational efficiency and lean manufacturing goals

Key Requirements

  • •Programming in Python
  • •Basic knowledge of machine learning and data analysis
  • •Understanding of physics principles related to sensing and measurement
  • •Familiarity with data visualization tools and ability to interpret experimental results
  • •Familiarity with machine learning workflows and ML DevOps best practices
Education:
Skills:Stakeholder engagementProcess improvementData collectionAnalysisPresenting recommendations
Tech Stack:PythonMachine learningData analysisData visualization toolsML DevOpsModel governancePredictive modelsClustering algorithmsSignal processing

Company Brief

Applied Materials
Provides semiconductor manufacturing equipment, services, and software used to build advanced chips and display technologies. Its tools support materials engineering, deposition, etching, inspection, and process control for major electronics manufacturers worldwide.
Industry: Industrial Machinery
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1967
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Glassdoor: 3.9
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