Principal Software Development Engineer, Mlops

Workday

Toronto, ON, CA
Base: $168,000 - $252,000 cad; bonus/equity: eligi...
Fully remote
Mlops platform development
Python and go programming
Infrastructure as code with terraform
As a Principal Software Engineer, you will build ML-powered features and infrastructure that impact millions of users across Workday’s HR & Talent products

Job Summary

  • As a Principal Software Engineer, you will build ML-powered features and infrastructure that impact millions of users across Workday’s HR & Talent products.
  • You will work with multi-functional teams to deliver scalable, secure, and reliable MLOps solutions using cutting-edge cloud and ML technologies.
  • Workday offers a flexible work approach combining remote and in-person time, with comprehensive benefits and a culture rooted in integrity, empathy, and shared enthusiasm.

Matching Summary

As a Principal Software Engineer, you will build ML-powered features and infrastructure that impact millions of users across Workday’s HR & Talent products.

Salary

Base: $168,000 - $252,000 CAD; Bonus/Equity: Eligible for bonus and stock grants; Benefits: Comprehensive benefits package

Skills & Requirements

Must-have

  • MLOps platform development
  • Python and Go programming
  • Infrastructure as code with Terraform
  • Kubernetes cluster management
  • Cloud computing with AWS and GCP
  • Microservices and API development
  • Kubeflow for ML pipelines

Nice-to-have

  • Leadership and mentoring experience
  • Familiarity with LangChain and LangSmith
  • Experience with Databricks, Sagemaker, or Spark
  • Strong problem-solving and creative thinking
  • Empathy and collaborative culture
  • Flexible work environment
  • Knowledge of agentic AI systems

Key Requirements

  • 6+ years industry experience
  • Bachelor’s or Master’s in Computer Science or Engineering
  • Experience designing scalable AI/ML platforms
  • Proficiency in Python, Go, and Terraform
  • Deep understanding of cloud infrastructure and distributed systems
  • Experience with Kubernetes in production
  • Knowledge of CI/CD workflows for ML
  • Familiarity with agentic AI concepts

Work Rights

Not specified

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