Software Engineer, ML Ops

In this role you will run secure developer environments, own container image build and CI/CD tooling, and instrument training code with self-service debugging. You will set infrastructure best practices, document AI enablement, and support researchers and ML engineers as the platform scales. You’ll troubleshoot production issues and build automation to keep the system maintainable. This role combines hands-on platform work with collaboration across an AI research-to-inference workflow, in a remote-friendly, multi-office environment.

• Weekly lunch stipend
• Health and dental benefits
• RRSP matching / Pension
• 6 weeks of paid vacation
• Parental leave top-up
• Learning stipend / education budget

• Run secure developer environments to accelerate developer velocity
• Own container image build and CI/CD tooling
• Instrument training code and build self-service debugging tooling
• Set infrastructure best practices through AI enablement, documentation, and office hours
• Troubleshoot production failures and performance issues to improve operability
• Build automation, infrastructure-as-code, and observability to maintain the platform

• Experience running a developer platform in production: CI, image builds, dev environments, or internal tooling
• Made ML engineers or researchers faster without making the platform fragile
• Proficiency with Linux and Kubernetes for debugging production systems
• Experience with Python or Go
• Preference for contributing to open-source projects over rebuilding from scratch
• Collaborated with researchers, ML engineers, or teams with not-identical goals
• Identified bottlenecks and drove fixes in a fast-moving environment

• Cross-functional collaboration
• Proactive debugging and problem-solving
• Adaptability in a fast-moving environment
• Linux
• Kubernetes
• Python