Forward Deployed SRE
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.
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.
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