DevOps Engineer

12 hours ago

uttar pradesh, India Techmates Technologies Full time

We're seeking a hands-on DevOps / Cloud Engineer who can own our infrastructure end-to-end and support a fast-moving ML engineering team. You will design, build, and operate the cloud, data, and deployment systems that power our product — with a strong emphasis on reliability, automation, security, and speed.What You'll DoDesign & manage cloud infrastructure (AWS / GCP / Azure) for core services, data pipelines, and ML workloadsBuild CI/CD pipelines for backend systems, ML model training/inference, and microservicesDeploy & optimize ML clusters — GPU nodes, autoscaling, Docker/Kubernetes-based workloadsImplement observability: metrics, logs, traces, alerting, SLOsOwn Infrastructure-as-Code (Terraform, CDK, Helm) for all environmentsImprove developer velocity through automated builds, tests, deploy tools, and internal platform enhancementsEnsure security best practices: IAM, secrets management, VPC/networking, least-privilegeParticipate in on-call rotation and support incident response for production systemsWhat You BringStrong experience with AWS/GCP (EKS/GKE, EC2, VPC, IAM, S3/Cloud Storage)Deep expertise in Docker & Kubernetes, including GPU-aware orchestrationHands-on experience with CI/CD systems (GitHub Actions, GitLab CI, Argo, Jenkins)Knowledge of MLOps tooling: model serving, feature pipelines, artifact/versioning (MLflow, Weights & Biases, KServe, Ray)Solid Python or Go skills for automation toolingExperience with monitoring & logging stacks (Prometheus, Grafana, ELK/EFK, OpenTelemetry)Startup mindset: move fast, debug chaos, own outcomes end-to-endNice-to-HavesExperience with distributed training (Ray, Horovod, PyTorch Distributed)Security hardening, cost optimization, and infrastructure scaling expertiseExperience setting up GPU clusters (NVIDIA drivers, CUDA, MIG, Triton, Slurm/Ray clusters)

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