1 day ago
Base Salary
$165k - $330k/yr
Responsibilities
- Design, build, and operate services, APIs, and Kubernetes controllers for cluster lifecycle management.
- Develop reusable Terraform modules and GitOps configuration across cloud and GPU infrastructure providers.
- Implement validation, staged rollouts, ownership boundaries, and recovery paths for safe infrastructure changes.
- Build observability into automation to support progress tracking, failure diagnosis, and safe retries.
- Partner with infrastructure and workload teams to define platform interfaces and deliver projects from design through adoption.
Requirements
- Experience building and owning production infrastructure software or distributed systems.
- Strong programming skills in Go or another systems or backend language, with the ability to contribute to a Go codebase.
- Deep Kubernetes infrastructure experience, including controllers or operators, reconciliation, custom resources, and failure handling.
- Practical infrastructure-as-code and GitOps experience with tools such as Terraform, Flux, or Argo CD.
- Strong Linux, networking, debugging, and production-reliability fundamentals.
- Ability to turn ambiguous operational problems into maintainable software and communicate design tradeoffs clearly.
- Preferred experience includes managing Kubernetes fleets across multiple clouds or GPU infrastructure providers.
- Preferred qualifications include Kubernetes or infrastructure open-source contributions and experience with workflow orchestration or progressive delivery.
Benefits
- 100% medical, dental, and vision insurance coverage for U.S. employees and dependents.
- Flexible PTO and a company-wide Winter Break from Christmas Eve through New Year's Day.
- Paid parental leave.
- Fertility and family-building stipend through Carrot.
- Company-facilitated 401(k) for U.S. employees.
- Exposure to a variety of ML startups and related learning and networking opportunities.
About Baseten
Baseten builds an AI inference platform that provides tooling, infrastructure, and hardware to deploy, scale, and serve machine-learning models in production. The company sells managed model serving and developer tooling to software teams at AI product companies, with customers including Notion, Abridge, Writer, and Cursor. Privately held and headquartered in San Francisco, it focuses on high-availability, globally distributed inference for production workloads.