{"id":750448,"url":"https://alion.io/job/bitdeer-technologies-group-sr-gpu-cloud-k8s-expert-sre-sme-2","title":"Sr GPU Cloud K8S Expert (SRE SME)","company":{"id":174995,"name":"Bitdeer Technologies Group","domain":"bitdeer.com","url":"https://alion.io/company/bitdeer","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Breezy","truth_index":{"grade":"B","score":79,"open_postings":13,"ghost_share":0,"stale_share":0.846,"repost_share":0,"time_to_fill_p50_days":39,"computed_at":"2026-10-29T05:49:05Z"}},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Jose, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":115000,"max_usd":215000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":395},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AIOps","optional":false},{"name":"Alertmanager","optional":false},{"name":"ArgoCD","optional":false},{"name":"Bitcoin","optional":false},{"name":"GitOps","optional":false},{"name":"Go","optional":false},{"name":"Grafana","optional":false},{"name":"Helm","optional":false},{"name":"Incident Management","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"NVLink","optional":false},{"name":"PagerDuty","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"Ray","optional":false},{"name":"Self-Healing","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"SLURM","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-09-11T14:13:59Z","employer_posted_date":"2026-09-11","last_verified_at":"2026-10-29T15:09:42Z","board_verified":true,"closed_at":null,"days_open":48,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":48},"description":"Bitdeer is a world-leading technology company for AI and Bitcoin mining infrastructure.\nBitdeer is committed to providing comprehensive Bitcoin mining solutions for its customers and building AI computational infrastructure to support the AI revolution. Bitdeer handles complex processes involved in computing such as equipment procurement, transport logistics, data center design and construction, equipment management, and daily operations. Bitdeer also offers advanced cloud capabilities to customers with high demand for artificial intelligence.\nHeadquartered in Singapore, Bitdeer has deployed data centers across multiple countries, including the United States, Norway, Bhutan, and Ethiopia.\nTo learn more, visit https://ir.bitdeer.com/\nPosition Overview\nYou run the control plane where AIOps meets tenants - where topology-aware scheduling, self-healing, and agent-driven remediation actually execute.\nNeoCloud is building an AI-operated GPU cloud. Kubernetes is where all of that lands on real customer workloads: the topology-aware scheduler places jobs on the right NVLink domain, the operator drains and reschedules around predicted faults, and the tenant boundary is enforced against a Bare-Metal-as-a-Service backend. In this role you design, deploy, and operate that control plane - and you make sure the AIOps substrate can reach in and remediate without a human on the pager.\nWhat you'll own\nProduction Kubernetes clusters optimized for GPU workloads at scale (100-10,000 GPUs).\nNvidia GPU operator, device plugin, MIG configuration, and GPU time-slicing policies.\nTopology-aware scheduling: GPU locality, NVLink domain awareness, network rail affinity.\nCustom Resource Definitions (CRDs) for GPU workload lifecycle management.\nAI framework integrations: Slurm on K8S, Ray on K8S, Kubeflow.\nMulti-tenant isolation: namespaces, network policies, resource quotas, RBAC, pod security standards.\nBare-Metal as a Service (BMaaS): automated provisioning, tenant onboarding, lifecycle, reclamation.\nTerraform providers and modules for infrastructure-as-code across GPU clusters.\nSLIs/SLOs for cluster availability, job completion rates, and provisioning latency.\nIncident management: runbook automation, escalation, post-incident reviews.\nMonitoring stack: Prometheus, Grafana, Alertmanager, PagerDuty.\nGPU node failure handling: automated detection, drain/cordon/taint, workload rescheduling.\nFeed the AIOps substrate\nThe remediation-actuator and workflow engine land here - you make the control plane safe for automated action.\nYour CRDs are the schema the platform's predictors and remediators write against.\nEvery human intervention you do this quarter becomes an autonomous workflow next quarter.\nWhat success looks like in year 1\nAutomated drain/reschedule around predicted GPU faults, at scale, without customer impact.\nBMaaS live for external tenants with self-service onboarding.\nCluster availability and job-completion SLOs published and met.\nJob Requirement:\n5+ years in Kubernetes operations, with at least 2 years managing GPU workloads on K8S\nDeep understanding of Nvidia GPU operator, device plugin, and GPU scheduling in K8S\nExperience with topology-aware scheduling and GPU-specific resource management\nHands-on experience building multi-tenant K8S platforms with strong isolation guarantees\nExperience with bare-metal server provisioning and lifecycle automation (Ironic, MAAS, or custom)\nProficiency in Terraform, Helm, and GitOps workflows (ArgoCD/Flux)\nStrong SRE background: SLI/SLO frameworks, incident management, capacity planning\nExperience with Prometheus, Grafana, and alerting at scale\nStrong programming skills in Go or Python for operator/CRD development\nAIOps aptitude - you think of the K8S control plane as an execution surface for automated remediation, not just a scheduler. You've either wired an autoscaler/remediator loop into K8S or you can design one.\nRunbook-as-code mindset - every SRE playbook you write should be executable by the platform.\n--------------------------------------------------------------------\nBitdeer is committed to providing equal employment opportunities in accordance with country, state, and local laws. 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