Senior ML Engineer & MLOps Architect — Scale AI Systems

Index Exchange

Toronto

On-site

CAD 120,000 - 180,000

Full time

14 days+

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Benefits offered by this job

Health, dental, vision plans
Generous parental leave
Equity packages
Well-being allowance
Volunteering time off
Commuter benefits
Learning resources and training

Job summary

Index Exchange in Toronto is seeking a Senior Machine Learning Engineer to guide ML/optimization strategy and drive pragmatic execution at scale. You will shape end-to-end ML lifecycle and enable fast, reliable, low-latency inference across our platform.

The role emphasizes enterprise ML deployment, data-management optimization, and mentoring teams to elevate engineering practices with CI/CD and modern ML tooling.

Qualifications

  • Advanced degree in Computer Science, Engineering, or related field.
  • Expertise in high-performance backend technologies, preferably including Golang.
  • Extensive experience with cloud/on-prem distributed systems and large-scale backend design.
  • Deep knowledge of ML operationalization, tools and frameworks.

Responsibilities

  • Design and implement enterprise-scale MLOps systems and platforms with high performance.
  • Productionalize scalable ML models and solutions.
  • Define and enforce standards for model lifecycle management and low-latency inference.
  • Refine data management strategies for large data loads and performance.
  • Mentor teams and promote best practices for ML deployment.
  • Enable safe deployment strategies such as shadow, canaries, and gradual rollout.

Skills

MLOps
Model deployment
CI/CD
Distributed systems
Golang
ML engineering
Mentoring
Performance optimization

Education

Advanced degree in CS/Engineering

Job description

Index Exchange in Toronto is seeking a Senior Machine Learning Engineer to guide ML/optimization strategy and drive pragmatic execution at scale. You will shape end-to-end ML lifecycle and enable fast, reliable, low-latency inference across our platform.

The role emphasizes enterprise ML deployment, data-management optimization, and mentoring teams to elevate engineering practices with CI/CD and modern ML tooling.

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