Senior Platform Engineer

As a Senior Platform Engineer you design and operate a production-grade Kubernetes-based AI/ML platform that enables MLOps teams, ML engineers and data scientists to deploy and manage models at scale. You build infrastructure, tooling, and guardrails to support reliable, repeatable model deployment and scalable inference. You own platform operability, security, and lifecycle in production and collaborate closely with data scientists to ensure the platform is genuinely usable. This role offers impact by shaping robust AI/ML workflows at scale.

• Design, build, and operate a Kubernetes-based platform supporting multiple ML and engineering teams
• Extend Kubernetes with MLOps-specific capabilities
• Provide platform-level support for model development, packaging, deployment, and promotion
• Support scalable inference and LLM-based workloads
• Build shared platform services enabling consistent model deployment
• Collaborate with data scientists and MLOps engineers to ensure usability
• Own platform operability, reliability, security, and lifecycle management in production
• Troubleshoot cross-cutting issues across infrastructure, Kubernetes, and MLOps
• Contribute to architectural decisions while remaining hands-on

• Senior Platform Engineer or Senior DevOps Engineer background
• Hands-on Kubernetes-based platform experience
• Practical experience with Helm and Terraform (IaC)
• Experience building internal platforms for engineers
• Strong monitoring, logging, reliability, incidents, and maintainability fundamentals
• Collaborative with MLOps engineers and data scientists
• ML platform & MLOps knowledge
• Understanding of ML/AI workloads in production
• Exposure to MLOps platforms (Kubeflow or similar), model serving/inference platforms (KServe, vLLM), and notebook environments (JupyterHub)
• Awareness of Responsible/Trustworthy AI tooling

• collaboration
• problem-solving
• clear communication
• Kubernetes
• Helm
• Terraform