Site Reliability Engineer owns reliability of multi-cloud Kubernetes infrastructure for AI/ML platform, builds observability tooling as code, automates mitigations, leads incident response, and defines SLOs/SLIs. Requires extensive Kubernetes and observability experience.
135k – 285k/yr
HybridDevOps / SRE
About the role
Responsibilities
Own the reliability of Baseten's multi-cloud Kubernetes infrastructure, including incident response, post-mortems, and remediation tracking.
Build and maintain observability infrastructure — metrics, logging, dashboards, and alerting — as code.
Author, validate, and improve runbooks for recurring failure patterns, ensuring they're structured for low-context, safe execution.
Identify high-frequency failure patterns and convert them into automated mitigations or self-healing automations.
Diagnose and resolve runtime issues related to latency, memory behavior, GPU utilization, concurrency, and model lifecycle management.
Define and instrument SLOs and SLIs across customer workloads and internal services.
Navigate ambiguity, make principled tradeoffs, and avoid unnecessary complexity in the systems you build and the processes you define.
Requirements
Extensive hands-on experience with Kubernetes (multi-cloud experience across EKS, GKE, or similar is a strong plus).
Experience in building and maintaining scalable infrastructure.
Strong foundation in observability tooling: metrics (VictoriaMetrics, Prometheus), logging (Loki, ELK), dashboards (Grafana), and alerting pipelines. Observability-as-code experience is a plus.
Experience with infrastructure-as-code (Terraform, Helm) and GitOps workflows (Flux CD, ArgoCD).
Experience writing and improving runbooks, leading incident response, and doing post-mortem analysis.
Comfort working at the intersection of engineering and operations — you write code, but you also think deeply about process, escalation paths, and operational leverage.
Familiarity with incident management platforms (incident.io or similar) is a plus.
No prior ML experience required, but curiosity about how ML models are deployed and served at scale will serve you well.
Benefits
Competitive compensation, including meaningful equity.
100% coverage of medical, dental, and vision insurance for employee and dependents.
Flexible PTO policy including company wide Winter Break.
Paid parental leave.
Fertility and family-building stipend through Carrot.
Company-facilitated 401(k).
Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
Skills
KubernetesPrometheusGrafanaTerraformHelmEKSGKEVictoriametricsLokiArgo CD
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