Senior MLOps Engineer

Deep Genomics is using AI to transform drug discovery. They are seeking a Senior MLOps Engineer to own and evolve infrastructure for ML pipelines, working closely with ML scientists and engineers to ensure reliability and scalability.

• 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). Operate and configure ML experiment tracking and registry tooling (e.g., W&B, MLflow). 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. Help deploy ML models to production environments and monitor their performance.

• 4+ years of experience operating production infrastructure. Proficiency with cloud platforms (GCP preferred; AWS/Azure acceptable) and Infrastructure-as-Code (Terraform). Extensive hands-on experience with Kubernetes and containerization (Docker). Solid background in CI/CD systems (CircleCI, GitHub Actions, or similar). Experience managing GPU compute (provisioning, debugging, driver management). Familiarity with Python package and environment management (e.g., pip, conda, pixi). Strong Python programming skills. Self-motivated problem solver with excellent communication skills.