Lead DevOps​/MLOps Engineer

We’re looking for a strong Dev Ops engineer who can help scale and operationalize our infrastructure as the platform grows. This is not a pure platform-architecture role — the focus is CI/CD, infrastructure automation, deployment reliability, observability, and GPU-oriented workload scaling.

• Improve CI/CD pipelines, deployment workflows, and release reliability
• Standardize infrastructure and deployment patterns across environments
• Improve observability through logging, metrics, tracing, dashboards, and rollout monitoring
• Partner closely with backend engineering on:
  • deployment strategies
  • infrastructure automation
  • environment consistency
  • migration workflows
  • possible Kubernetes migration efforts
• Support ML-oriented infrastructure as a secondary responsibility:
  • Sage Maker workloads
  • Ray clusters
  • GPU scaling patterns
  • distributed batch execution
  • autoscaling behavior
  • runtime/image management
  • artifact delivery/versioning

• Deployment safety and rollback strategies
• Infrastructure consistency across environments
• Release automation and environment promotion flows
• Autoscaling and runtime stability
• GPU workload orchestration and scaling efficiency
• Operational tooling that reduces friction for engineering teams

• AWS
• Terraform
• Docker
• Kubernetes
• CI/CD systems
• Sage Maker
• Ray
• GPU compute infrastructure

• You’ve operated production infrastructure at meaningful scale
• You’re strong in practical Dev Ops execution and operational reliability
• You care about automation, observability, and deployment safety
• You’re comfortable improving developer workflows and infrastructure tooling
• You’ve worked with distributed systems or GPU-oriented workloads before