Job Description

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and enterprise clients.

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

Qualifications:

• 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

Preferred:

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

Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law.

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