Deep Genomics

Deep Genomics

Senior MLOps Engineer

Toronto, Ontario · Senior

Sponsorship not specified$175k-$200kDetected 103 days ago
PythonNode.jsGitAWSGCPAzureCloud PlatformsDockerKubernetesTerraformCI/CDGitHub ActionsCircleCIMachine LearningPyTorchData ScienceMLOpsAI OrchestrationComplianceHIPAABioinformaticsResearchCommunication

About the role

  • With expertise spanning machine learning, bioinformatics, data science, engineering, and drug development, our multidisciplinary team in Toronto and Cambridge, MA is revolutionizing how new medicines are created.
  • Ideal Candidate You are someone who enjoys keeping the infrastructure running smoothly so that scientists can focus on their research.
  • You are comfortable working across cloud platforms, CI/CD systems, containers, and GPUs - and you take pride in making these systems reliable and easy for others to use.

Responsibilities

  • Maintain and improve cloud infrastructure (GCP) using Infrastructure-as-Code tools (Terraform).
  • Manage IAM, RBAC, and permission policies across cloud environments.
  • Own and evolve CI/CD pipelines (CircleCI, GitHub Actions) and ensure best practices are followed across the engineering and ML teams.
  • Administer and support workflow orchestration platforms (e.g., Seqera/Nextflow, Argo, Kubeflow).
  • Build and maintain containerized environments (Docker) and manage Kubernetes clusters.
  • Manage GPU resources - provisioning, scheduling, and debugging hardware and driver issues.
  • Write and maintain Python tooling, scripts, and integrations that support ML infrastructure.
  • Deep Genomics encourages applications from all backgrounds who seek the opportunity to build the world's leading AI-driven genetic medicine company.

Requirements

  • 4+ years of experience operating production infrastructure.
  • Extensive Hands-on experience with Kubernetes and containerization (Docker).
  • Experience managing GPU compute (provisioning, debugging, driver management).
  • Familiarity with Python package and environment management (e.g., pip, conda, pixi).

Nice to have

  • Understanding of ML frameworks (e.g., PyTorch, PyTorch Lightning), ML workflows (training, inference, evaluation), and the model lifecycle.
  • Familiarity with MLOps tooling (e.g., W&B, Ray, VertexAI) and distributed compute patterns
  • (e.g., DDP, realtime/batch inference, multi-node training).
  • Familiarity with Kubernetes CRDs and batch/gang schedulers (e.g., Volcano, Kueue).
  • Experience working with large-scale datasets (storage, versioning, efficient access patterns).
  • Experience working directly with scientists and researchers in an interdisciplinary setting.
  • Familiarity with data compliance and governance frameworks (e.g., HIPAA, SOC 2).
  • Previous startup experience.

Compensation

  • The salary range for this role is $175,000 - $200,000, and reflects Canada-based roles
  • The salary range for this role is $175,000 - $200,000, and reflects Canada-based roles; compensation may differ for U.S.-based candidates.

Benefits

  • A collaborative and innovative environment at the frontier of computational biology, machine learning, and drug discovery.
  • Highly competitive compensation, including meaningful stock ownership.
  • Comprehensive benefits - including health, vision, and dental coverage for employees and families, employee and family assistance program.
  • Flexible work environment - including flexible hours, extended long weekends, holiday shutdown, unlimited personal days.
  • Maternity and parental leave top-up coverage, as well as new parent paid time off.
  • Focus on learning and growth for all employees - learning and development budget & lunch and learns.
  • Facilities located in the heart of Toronto - the epicenter of machine learning and AI research and development, and in Kendall Square, Cambridge, Mass. - a global center of biotechnology and life sciences.

Company info

  • Deep Genomics is at the forefront of using artificial intelligence to transform drug discovery.
  • Our proprietary AI platform decodes the complexity of RNA biology to identify novel drug targets, mechanisms, and therapeutics inaccessible through traditional methods.
  • Opportunity Join us in building the future of AI-driven drug discovery as a Senior MLOps Engineer.
  • You will own and evolve the infrastructure that powers our ML pipelines - from cloud environments and CI/CD systems to workflow orchestration and model deployment.
  • You will work closely with ML scientists, bioinformaticians, and software engineers to keep our platform reliable, reproducible, and scalable.
  • You have 4+ years of experience in production infrastructure or MLOps, you write solid Python, and you are curious about the ML and scientific workflows your work supports.
  • Above all, you are a collaborative, kind team member who communicates clearly, adapts to evolving needs, and is happy to help colleagues grow their own infrastructure skills along the way.
  • If this sounds like you, we would love to hear from you.
  • We offer competitive compensation aligned with local market benchmarks.

Equal opportunity

  • If you have a disability or special need, accommodation is available on request for candidates taking part in all aspects of the selection process. *This posting reflects a current vacancy.
Apply directly at Deep Genomics →Create a free account for alerts like thisView Deep Genomics immigration profile

This listing is sourced directly from Deep Genomics's careers page and normalized into a canonical job model.