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Job Description About The Role We're a fast-moving startup building a high-traffic communication product and production-grade ML models. We're looking for a language-agnostic Dev Ops Lead to take complete ownership of our infrastructure from scratch cloud environments, secure architectures, CI/CD, observability, and developer tooling that backend and ML engineers rely on daily. Responsibilities - Architect, provision, and scale cloud infrastructure across GCP/AWS/Azure for both web backends and compute-intensive ML workloads - Establish cloud accounts from scratch with strict IAM policies, RBAC, and secure networking (VPCs, subnets, peering) - Build robust, language-agnostic CI/CD pipelines using Git Hub Actions, Jenkins, or Git Lab CI for secure multi-environment deployments - Containerize and orchestrate applications using Docker, Kubernetes, and Helm - Deploy and manage Matrix homeserver infrastructure (Synapse/Dendrite) including federation, workers, and database setup - Build observability from a blank slate monitoring, logging, alerting using Prometheus, Grafana, ELK, or Datadog - Instrument applications for deep insights into API performance, system health, and ML model inference metrics - Manage infrastructure as code with Terraform or Pulumi version-controlled, repeatable, cloud-agnostic - Collaborate with software engineers and ML researchers to remove deployment bottlenecks and maintain developer velocity Requirements - 8+ years in Dev Ops, SRE, or Cloud Infrastructure with holistic infrastructure ownership - Language-agnostic comfortable navigating Python, Go, Node.js, Java codebases for tooling and instrumentation - Deep hands-on experience with Kubernetes, Docker, and Helm in production - Strong IaC proficiency (Terraform or Pulumi) - Extensive CI/CD pipeline experience (Git Hub Actions, Jenkins, Git Lab CI) - Security-first mindset cloud networking, IAM/RBAC, secrets management - Proven ability to build monitoring/logging stacks from scratch - Builder's mentality comfortable starting with a blank canvas and making authoritative architectural decisions Nice to Have - Experience with MLOps GPU provisioning, model registry integration, inference pipeline deployment - Familiarity with Matrix protocol infrastructure (Synapse/Dendrite federation and worker architectures) - Experience with MongoDB, PostgreSQL, Neo4j, and Redis in cloud environments - Frontend deployment experience (CDN, static hosting, SSR) .
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