MLOps Engineer - Remote
Tasks
- Administer Kubernetes and GKE
- Automate systems with Bash, Python, Go
- Communicate best practices effectively
- Connect notebooks with Big Data infrastructure
- Create CI/CD pipelines using Jenkins, CircleCI, GCP Build
- Create and deploy ML notebooks
- Create guides for Git CI/CD
- Develop MLOps best practices
- Dockerize ML scripts and deploy on GCP
- Implement experiment tracking
- Improve system performance and reliability
- Manage Helm manifests
- Manage model registry and ML pipelines
- Monitor production drift and alerting
- Optimize cloud compute resources
- Provision and configure cloud infrastructure
- Setup monitoring and alerts in GCP
- Share knowledge on system operations and cloud strategies
- Use configuration/deployment tools like Terraform, Deployment Manager
- Utilize Puppet, Ansible, Chef, Packer for automation
- Work in agile environments
- Write processed data to data lakes and warehouses
Perks/Benefits
- N/A
Skills/Tech-stack
Agile | Ansible | Automation | Bash | CI/CD | Chef | CircleCI | Cloud | Deployment Manager | Docker | Experiment tracking | GCP | Git | Go | Google Deployment Manager | Helm | Jenkins | Kubernetes | ML pipelines | MLOps | Model Registry | Monitoring | Packer | Puppet | Python | Statistical Testing | Terraform
Education
Bachelor's | Master's | PhD
Roles
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