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Machine Learning Quality Engineer

Machine Learning Quality Engineer

CompanyServiceNow
LocationSanta Clara, CA, USA
Salary$123500 – $191500
TypeFull-Time
Degrees
Experience LevelJunior, Mid Level

Requirements

  • Experience in quality assurance and/or application development
  • Strong test automation skills in Java / Python
  • Hands-on experience testing large-scale, production systems in Python or Java
  • Excellent communication, reporting and problem-solving skills
  • Ability to take a project from scoping the requirements and building the test cases
  • Maintain existing automation test frameworks
  • Familiarity with testing AI/ML models and evaluation of the model quality
  • Ability to review results from the test set and create defects based on result patterns
  • Work with developers to design specific testing strategies for features being developed and automate them
  • Create comprehensive test plans; execute and automate them
  • Partner with the engineering organizations in troubleshooting or addressing issues with applications and dev/test environments

Responsibilities

  • Create comprehensive test plans; execute and automate them
  • Maintain existing automation test frameworks
  • Work with developers to design specific testing strategies for features being developed and automate them
  • Partner with the engineering organizations in troubleshooting or addressing issues with applications and dev/test environments

Preferred Qualifications

  • Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving
  • 2+ years of experience with technologies relevant to SN, Quality engineering and coding skills with high-quality results
  • 2 years of experience as a Machine Learning Quality Engineer
  • Experience working within different automated testing frameworks, including Java, JUnit, Python, Selenium, TestNG and other open-source projects
  • Experience with the agile methodology for software development teams
  • Ability to know several testing techniques (e.g. performance, unit, integration, automated), their strengths and weakness, and ability to use them to best effect – including tracking and addressing of any discovered issues
  • Ability to use tools (such as IDE, debugger, build tools, source control, ServiceNow instances, profilers, system administration/Unix tools) to assist with daily tasks