Machine Learning Engineer II

Qualtrics Qualtrics · Seattle · Seattle, WA · Core AI

Machine Learning Engineer II at Qualtrics to enhance AI/ML R&D strategy for personalizing customer experiences. The role involves developing and deploying ML models, building scalable microservices, and maintaining data pipelines for complex, multi-modal data. Focus on integrating advanced intelligence into user experiences within the Data Intelligence Center of Excellence (DICE) organization.

What you'd actually do

  1. Develop scalable, robust, and highly available micro services to perform simple to complex statistical analyses and build/deploy machine learning models
  2. Implement new features and optimize existing ones to delight our customers
  3. Build and maintain highly scalable data pipelines to cleanse, anonymize, measure, and index complex and multi-modal data.
  4. Work closely with, and incorporate feedback from other specialists, tech-ops, and product managers
  5. Lead and engage in design reviews, architectural discussions, requirement definitions and other technical activities in diverse capacity

Skills

Required

  • Bachelor’s degree in Computer Science or related fields.
  • 2-5 years of experience as a Machine Learning Engineer
  • Strong Computer Science fundamentals in algorithm design, complexity analysis, and performance
  • Experience in programming with at least one modern programming language such as Java, C# or Python, including object-oriented design
  • Experience with applied machine learning models and large-scale ML systems
  • TensorFlow or PyTorch

Nice to have

  • Stay up-to-date with industry trends and academic research to evaluate new tools, frameworks, and modeling techniques.

What the JD emphasized

  • strong track record in designing, implementing, and optimizing machine learning models for real-world applications
  • Experience with applied machine learning models and large-scale ML systems

Other signals

  • personalize the Qualtrics experience using ML and AI features
  • showcasing Qualtrics data as a core value proposition and competitive advantage
  • Develop scalable, robust, and highly available micro services to perform simple to complex statistical analyses and build/deploy machine learning models
  • Implement new features and optimize existing ones to delight our customers
  • implement, tune, and productize cutting-edge machine learning models
  • Build and maintain highly scalable data pipelines to cleanse, anonymize, measure, and index complex and multi-modal data.