Principal Site Reliability Engineer (Intelligent Automation)
South San Francisco, United States
USD 162K-302K Senior-level Full Time
Tasks
- Automate deployment of ML pipelines and HPC clusters
- Build resilient highly available architectures for ML and HPC
- Design and implement infrastructure as code solutions
- Develop automation scripts and workflows for infrastructure management
- Ensure security governance and regulatory compliance
- Implement disaster recovery and business continuity
- Lead AIOps incident management
- Mentor and train engineers in IaC and HPC
- Monitor and optimize cloud usage and costs
- Partner with cross functional teams to align solutions to business goals
- Provide technical leadership to engineers
- Provision and manage cloud infrastructure for ML and HPC workloads
- Run chaos engineering experiments
- Set up monitoring logging and alerting
Perks/Benefits
- N/A
Skills/Tech-stack
AIOps | AWS | Auto Scaling | Azure | Bash | Business Continuity | CI/CD | Chaos Engineering | Cloud platform | CloudFormation | Data Pipelines | Datadog | Disaster Recovery | Distributed Systems | ELK Stack | Feature Store | GPU Computing | Go | Google Cloud | Google Cloud Platform | Grafana | HPC | Infrastructure as Code | Kubernetes | Load Balancing | MLOps | Machine Learning | Machine Learning Pipelines | Model Deployment | Model Monitoring | Model versioning | Multi-region | Multi-region Deployments | NVIDIA CUDA | Prometheus | Pulumi | Python | Reliability Engineering | Serverless computing | Site Reliability | Site Reliability Engineering | Spacelift | Storage Systems | TensorFlow | Terraform | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Regions
Countries
States
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