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Sr Director – Machine Learning Engineering – Machine Learning Engineering

Sr Director – Machine Learning Engineering – Machine Learning Engineering

CompanyQualcomm
LocationMarkham, ON, Canada
Salary$Not Provided – $Not Provided
TypeFull-Time
DegreesBachelor’s, Master’s, PhD
Experience LevelSenior, Expert or higher

Requirements

  • Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field and 10+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
  • Master’s degree in Computer Science, Engineering, Information Systems, or related field and 9+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
  • PhD in Computer Science, Engineering, Information Systems, or related field and 8+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

Responsibilities

  • Working with various engineering leads, QA leads, and project managers to define, lead and drive engineering projects involving the software development process and QA processes for a global AI software engineering team.
  • Work closely with various teams, including engineering, project management, product management, QA, DevOps, and verification, to streamline processes and improve efficiency while maintaining high quality.
  • Document processes and coordinate with stakeholders to ensure clarity and consistency.
  • Make informed decisions on behalf of the organization, taking into account the needs of multiple different business units and customers.
  • Continuously identify and implement improvements in model testing, exception approval processes, and build time optimization.
  • Provide technical support and guidance to developers using the processes and databases related to testing and developer workflows.
  • Drive innovation and continuous improvement within the engineering team.

Preferred Qualifications

  • Experience with AI model testing
  • Experience with Edge devices running trained AI models.
  • Familiarity with prioritization/exception management
  • Strong problem-solving and analytical skills.