Swish Analytics is hiring a
DevOps Engineer

Summary

Join Swish Analytics as a DevOps Engineer to develop, maintain, and implement Kubernetes clusters at scale for heavy ML workloads. Work closely with Data Science and Data Engineering teams to optimize and scale workloads on Kubernetes. Pioneer best practices for software deployment and code management.

Requirements

• 4+ years of experience working in a DevOps or DevSecOps role
• 4+ years building within AWS, including EKS, EC2, RDS, and other common AWS services using Terraform, Terragrunt or similar technologies
• 4+ years building CICD pipelines with Github Actions, Jenkins and ArgoCD
• 4+ years of experience managing, provisioning and maintaining distributed systems with containerization tools, including Kubernetes, Docker, Helm
• 2+ years of Python or Go experience
• Have a deep understanding of distributed systems including storage, networking, and security
• Have previous SRE or DevOps experience in managing customer-facing systems in a 24/7 environment
• Have worked with machine learning pipelines

Responsibilities

• Use your experience to develop, maintain and implement Kubernetes clusters at scale that are ready for heavy/spiky ML workloads
• Work closely with Data Science and Data Engineering teams to implement, optimize and scale workloads on Kubernetes using CI/CD, automation tools and scripting languages
• Help Data Science and Data Engineering develop and implement specialized infrastructure to deliver tools/software to improve the reliability and scalability of services
• Pioneer, implement, and enforce best practices for software deployment and code management
• Monitor the system and respond to incidents to maintain system SLO/SLA, review and follow up production incidents
• Provide on call work as needed

Preferred Qualifications

• Experience with ML Ops or similar
• Knowledge in advanced statistical methods