Senior ML Platform Engineer

Deep Genomics; Toronto; On-site; CAD 175,000 - 200,000; Full time

Benefits offered by this job

Stock options

Comprehensive benefits (health/vision)

Flexible work environment

Job summary

Deep Genomics in Toronto is seeking a Senior MLOps Engineer to own and evolve the infrastructure powering our ML pipelines. You will work with ML scientists, bioinformaticians, and software engineers to ensure reliable, reproducible, and scalable platforms.

You will manage cloud environments (GCP), CI/CD (CircleCI, GitHub Actions), and container orchestration (Kubernetes, Docker), while supporting GPU workloads and model deployment. A collaborative, growth-oriented team awaits.

Qualifications

• 4+ years of experience operating production infrastructure.
• Proficiency with cloud platforms (GCP preferred; AWS/Azure acceptable) and Terraform.
• Hands-on Kubernetes and containerization experience (Docker).
• Solid background in CI/CD systems (CircleCI, GitHub Actions, or similar).
• Experience managing GPU compute and driver issues.
• Strong Python programming skills.

Responsibilities

• Maintain and evolve cloud infrastructure (GCP) using IaC tools such as Terraform.
• Manage IAM, RBAC, and permission policies across cloud environments.
• Own and evolve CI/CD pipelines (CircleCI, GitHub Actions) for engineering and ML teams.
• Administer workflow orchestration platforms (Seqera/Nextflow, Argo, Kubeflow).
• Operate ML experiment tracking and registry tooling (W&B, MLflow).
• Build and maintain containerized environments (Docker) and manage Kubernetes clusters.
• Manage GPU resources – provisioning, scheduling, and debugging driver issues.
• Write Python tooling and integrations to support ML infrastructure.
• Assist deployment of ML models to production and monitor performance.

Skills

Cloud platforms

Kubernetes

CI/CD

Python

Collaboration

Tools

Terraform

Docker

CircleCI

GitHub Actions

W&B

MLflow

Seqera/Nextflow

Argo

Kubeflow

Job description

Deep Genomics in Toronto is seeking a Senior MLOps Engineer to own and evolve the infrastructure powering our ML pipelines. You will work with ML scientists, bioinformaticians, and software engineers to ensure reliable, reproducible, and scalable platforms.

You will manage cloud environments (GCP), CI/CD (CircleCI, GitHub Actions), and container orchestration (Kubernetes, Docker), while supporting GPU workloads and model deployment. A collaborative, growth-oriented team awaits.