Devops Engineer (CI/CD, Github actions, Docker, Kubernetes)

• The DevOps Engineer is responsible for designing, building, and operating a scalable, reliable, and cost-efficient Machine Learning (ML) platform that supports real-time data ingestion, large-scale model training, and high-volume model serving.
• This role partners closely with data science, product, and engineering teams to enable rapid experimentation, seamless deployment, and production-grade operations for ML solutions in a retail execution environment.

• Design, architect, implement, and operate cloud-native infrastructure for the Execution Machine Learning platform.

  
  

• Identify inefficiencies in cost, scalability, performance, and reliability; propose and implement improved solutions.

  
  

• Build and maintain CI/CD pipelines using GitHub Actions or similar tools.

  
  

• Implement and manage infrastructure as code (IaC) using Terraform.

  
  

• Manage and optimize Azure cloud services, including AKS, Virtual Networks, Storage Accounts, and Key Vault.

  
  

• Collaborate with data scientists to design scalable solutions for model development, training, deployment, and serving.

  
  

• Support containerized workloads using Docker and Kubernetes.

  
  

• Design and support real-time data pipelines and streaming architectures using Kafka and cloud integrations.

  
  

• Develop and maintain Python-based automation, tooling, and platform components.

  
  

• Ensure platform security, observability, reliability, and operational excellence.

  
  

• Design, architect, implement, and operate cloud-native infrastructure for the Execution Machine Learning platform.

  
  

• Identify inefficiencies in cost, scalability, performance, and reliability; propose and implement improved solutions.

  
  

• Build and maintain CI/CD pipelines using GitHub Actions or similar tools.

  
  

• Implement and manage infrastructure as code (IaC) using Terraform.

  
  

• Manage and optimize Azure cloud services, including AKS, Virtual Networks, Storage Accounts, and Key Vault.

  
  

• Collaborate with data scientists to design scalable solutions for model development, training, deployment, and serving.

  
  

• Support containerized workloads using Docker and Kubernetes.

  
  

• Design and support real-time data pipelines and streaming architectures using Kafka and cloud integrations.

  
  

• Develop and maintain Python-based automation, tooling, and platform components.

  
  

• Ensure platform security, observability, reliability, and operational excellence.

  
  

Our Values

If you want to know the heart of a company, take a look at their values. Ours unite us. They are what drive our success – and the success of our customers. Does your heart beat like ours? Find out here: Core Values

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.