Lead Machine Learning Engineer

3 weeks ago


Vancouver, British Columbia, Canada Canada Workday ULC Full time

About the Role

As a Machine Learning Engineer, you will play a pivotal role in driving the success of our products and user experiences. You'll collaborate closely with product managers, designers, architects, and engineers to integrate cutting-edge ML/AI capabilities into our platform.

About You

  • You thrive on tackling complex technical challenges.
  • You are a recognized expert in modern machine learning and AI technologies.
  • You possess the ability to lead the entire ML/AI workflow, from data preparation and model training to deployment and ongoing operations (MLOps).
  • You excel as a team player, enjoying collaborative environments where you can contribute to building comprehensive user experiences.
  • You are results-oriented with a strong understanding of backend and service development best practices.
  • You are passionate about maintaining high code quality and sharing development standards within the team.
  • You have a genuine desire to learn and continuously grow your engineering expertise.

We welcome applications for both Senior and Principal Machine Learning Engineer roles, based on your experience and qualifications.

Basic Qualifications - Principal Machine Learning Engineer

  • 10+ years of experience in machine learning engineering.
  • 5+ years of experience as a Data Scientist or in a similar role.
  • 5+ years of experience designing and maintaining robust ML systems with a focus on clean architecture.

Basic Qualifications - Senior Machine Learning Engineer

  • 7+ years of experience as an ML engineer.
  • 2+ years of experience as a Data Scientist or in a similar role.
  • 2+ years of leading technical and functional discussions.

Other Qualifications

  • A Master's degree or higher in Computer Science, Statistics, Mathematics, or a related field.
  • Experience working effectively within multi-functional teams and leading the development of substantial ML/AI features with a strong emphasis on non-functional requirements (accuracy, scalability, performance, monitoring, maintenance, security, etc.).
  • A proven understanding of Statistics, Machine Learning, Deep Learning, and Large Language Model (LLM) technologies.
  • Extensive knowledge and hands-on experience in building and evaluating ML models.
  • Excellent interpersonal skills with the ability to clearly communicate complex technical concepts.
  • Familiarity with common frameworks such as numpy, pandas, sklearn, tensorflow, pytorch, langchain, etc.


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