Backend Engineer, Modelops Infrastructure

What you will bring

• Significant professional experience in Python backend infrastructure and Pytorch.
  
• Experience in working on scalability and maintainability challenges
  
• Production experience with Terraform, Kubernetes, Docker, and preferably GCP or equivalent technologies.
  
• Experience with tritton backend and post-production monitoring of large language models ( >10GB)
  
• High interest in defining infrastructure for large-scale ML recommendation engines 
  
• A genuine passion for learning as you will be solving the challenges of today, tomorrow, and many years to come.
  

What you will bring

• Significant professional experience in Python backend infrastructure and Pytorch.
  
• Experience in working on scalability and maintainability challenges
  
• Production experience with Terraform, Kubernetes, Docker, and preferably GCP or equivalent technologies.
  
• Experience with tritton backend and post-production monitoring of large language models ( >10GB)
  
• High interest in defining infrastructure for large-scale ML recommendation engines 
  
• A genuine passion for learning as you will be solving the challenges of today, tomorrow, and many years to come.
  

• Play a key role in the design, implementation, and integration of product features;
  
• Solve technical infrastructure problems of high scope and complexity;
  
• Test, deploy, maintain, and improve ML infrastructure and software that uses these models;
  
• Help to define and improve our internal standards for style, maintainability, and best practices for a high-scale web environment;
  
• Collaborate with other ML engineers and advise on the MLOps architecture from an infrastructure perspective;
  
• Respond to feature availability incidents and provide support for service engineers with customer incidents.