Senior MLOps Engineer
Tasks
- Administer workflow orchestration platforms
- Build and maintain containerized environments
- Deploy ML models to production and monitor performance
- Maintain and improve cloud infrastructure
- Manage GPU resources
- Manage IAM and permission policies
- Operate and configure experiment tracking and model registry
- Own and evolve CI/CD pipelines
- Write and maintain Python tooling
Perks/Benefits
- Dental insurance
- Extended long weekends
- Flexible work hours
- Health insurance
- Holiday shutdown
- Learning and development budget
- Lunch and learns
- Maternity and Parental Leave Top-Up
- New parent paid time off
- Unlimited personal days
- Vision insurance
Skills/Tech-stack
Access Management | Argo | CI/CD | CircleCI | Cloud platform | Conda | Docker | GPU Computing | GitHub Actions | Google Cloud | Google Cloud Platform | HIPAA | Identity and Access Management | Identity and access | Kubeflow | Kubernetes | Kubernetes CRDs | Kubernetes RBAC | MLflow | NVIDIA CUDA | Nextflow | Pip | PyTorch | Python | Ray | SOC 2 | Seqera | Terraform | Vertex AI | Weights and Biases
Education
N/A
Roles
Engineer | MLOps Engineer | Senior MLOps | Senior MLOps Engineer
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