Cloud Platform Engineer

THE ROLE

As a Cloud Platform Engineer, you'll envision and build robust systems and processes that ensure our infrastructure is scalable, reliable, and efficient. This can range from automating deployments and monitoring systems to optimizing performance and managing incidents.

We all work closely with our users, learning from their past struggles in operationalizing ML, onboarding them onto our platform, and turning our learnings into ideas for improving Baseten.

EXAMPLE INITIATIVES

You'll get to work on these types of projects as part of our Infrastructure team

• Multi-cloud capacity management
• Inference on B200 GPUs
• Multi-node inference
• Fractional H100 GPUs for efficient model serving

RESPONSIBILITIES

• Build and maintain scalable infrastructure to support the deployment and operation of machine learning models.
• Establish standards and best practices for reliability and performance across the infrastructure.
• Automate processes when relevant, particularly for managing CI/CD pipelines.
• Own products and projects end-to-end, functioning as both an engineer and a project manager, with a focus on user empathy, project specification, and end-to-end execution.
• Collaborate with cross-functional teams to understand project requirements and translate them into technical solutions.
• Mentor junior team members and contribute to knowledge sharing within the organization.
• Navigate ambiguity and exercise good judgment on tradeoffs and tools needed to solve problems, avoiding unnecessary complexity.
• Demonstrate pride, ownership, and accountability for your work, expecting the same from your teammates.

REQUIREMENTS

• Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or related field.
• Extensive experience with Kubernetes.
• Experience in building and maintaining scalable infrastructure.
• Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation, Pulumi) and CI/CD tooling (e.g., GitHub Actions, GitLab CI, Circle CI, Jenkins).
• Relevant OSS observability experience (Prometheus, ELK stack, Grafana stack, OpenTelemetry) is a plus.
• Ability to own projects end-to-end, from project specification to execution.
• No prior machine learning experience required, but should be open to learning about it.