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Infrastructure Engineer

Tamarind Bio

San Francisco, CAFull-timeSeen 1mo agoStill listed 2 days ago

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At a glance

Compensation
No compensation found
Location
San Francisco, CA
Schedule
Full-time
Work Authorization
Not specified

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Job overview

Tamarind Bio seeks an Infrastructure Engineer to lead scaling of its machine learning inference system, architecting and maintaining infrastructure for 150+ biological models while handling unpredictable workloads in a fast‑paced startup environment.

Skills & qualifications

RequiredNice to have

Skills

Programming AutomationContainerizationOrchestrationCloud PlatformsScaling Production SystemsKubernetesInfrastructure as CodeMonitoring and ObservabilityGPU Workloads

Qualifications

Located in SF Bay Area or RelocateOnsite Expectation 5 Days Per Week in SF

Full job description

We're looking for an Infrastructure Engineer to lead the scaling of our machine learning inference system. You'll be responsible for architecting and maintaining infrastructure that serves 150+ biological ML models, scaling our platform several orders of magnitude to meet rapidly growing demand. You’ll work closely with the founders to design to the constraints of customer needs, unpredictable workloads, and unique Bio-ML models. You'll work with Kubernetes and other tools to orchestrate containerized workloads, optimize resource allocation, and ensure high availability across our model serving infrastructure. Most importantly, you should thrive in a fast-paced startup environment where you'll wear multiple hats, learn new technologies quickly, and help solve novel technical challenges. We value engineering judgment, problem-solving ability, and the capacity to build systems that can evolve with our growing needs. Requirements

  • Solid programming and automation skills
  • Experience with containerization and orchestration concepts
  • Cloud platform knowledge (AWS/GCP/Azure)
  • Located in the SF Bay Area or able to relocate to the Bay Area
  • Onsite expectation: Team currently onsite in SF ~5 days/week.

Preferred

  • Experience scaling production systems
  • Kubernetes experience
  • Infrastructure as code tools (Terraform, Pulumi)
  • Monitoring and observability tools
  • Experience with GPU workloads

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