DevOps Engineer

We’re looking for an experienced MLOps / DevOps Engineer to build and maintain the production infrastructure powering our ML systems. You’ll ensure reliability, scalability, and automation of model pipelines, CI/CD workflows, and cloud infrastructure. Responsibilities Build and maintain CI/CD pipelines for ML training, validation, and deployment Manage AWS infrastructure (SageMaker, ECS/EKS, Lambda, S3) Deploy and scale ML model serving and inference services Containerize services with Docker and manage Kubernetes environments Implement monitoring, logging, and alerting (Prometheus, Grafana, CloudWatch) Manage infrastructure with Terraform / IaC Requirements 6+ years in DevOps, SRE, or MLOps Strong experience with AWS cloud infrastructure Production experience with Docker and Kubernetes Experience with CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI, etc.) Strong Python scripting and automation skills Experience with monitoring and observability tools Nice to Have Experience with ML model serving (SageMaker, TorchServe, Triton) Knowledge of MLflow, Kubeflow, or MLOps platforms Experience with vector databases (Qdrant, Weaviate, Milvus) Familiarity with LLM infrastructure Tech Stack AWS • Terraform • Docker • Kubernetes • Python • MLflow • PostgreSQL • Qdrant • Prometheus • Grafana What We Offer High-impact role in a small, fast-moving team Ownership of the full ML infrastructure stack Work with modern AI and ML systems Remote-first environment