Resumo da vaga

Site Reliability Engineer

Requisitos e responsabilidades

Conteúdo da vaga extraído em seções para revisão mais rápida.

Details

  • Improve Baseten SRE Practices, by instrumenting SLOs and SLIs, improving alerting and observability for all services.
  • Building AI-assisted tooling for incident triage and response.
  • 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.
  • 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.
  • 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 (our offices are closed from Christmas Eve to New Year's Day!)
  • 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.
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StackKubernetes, SparkSkills principais
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