Platform Engineer - AI/ML Infrastructure (Kubernetes & Terraform)
$136k - $240k • USA - Remote • FullTime
Posted 3mo ago
About the job
Deepgram is seeking an experienced Platform Engineer to build and operate the hybrid infrastructure foundation for its advanced AI/ML research and product development. This role involves architecting, building, and running a platform that spans AWS and bare metal data centers, enabling teams to train and deploy complex models at scale. The focus is on creating a robust, self-service environment using Kubernetes, AWS, and Infrastructure-as-Code (Terraform), and orchestrating high-demand GPU workloads with schedulers like Slurm. The ideal candidate is passionate about building empowering platforms, enjoys creating automated solutions for complex infrastructure challenges, and thrives on optimizing hybrid infrastructure for performance, cost, and reliability.
Responsibilities
- Architect and maintain the core computing platform using Kubernetes on AWS and on-premise.
- Develop and manage infrastructure using Infrastructure-as-Code (IaC) with Terraform.
- Design, build, and optimize AI/ML job scheduling and orchestration systems, integrating Slurm with Kubernetes for GPU resource management.
- Provision, manage, and maintain on-premise bare metal server infrastructure for GPU computing.
- Implement and manage platform networking (CNI, service mesh) and storage (CSI, S3) solutions.
- Develop an observability stack (monitoring, logging, tracing) and create automation for operational tasks.
- Collaborate with AI researchers and ML engineers to understand infrastructure needs and build accelerating tools.
- Automate the lifecycle of single-tenant, managed deployments.
Requirements
- 5+ years of experience in Platform Engineering, DevOps, or Site Reliability Engineering (SRE).
- Proven, hands-on experience building and managing production infrastructure with Terraform.
- Expert-level knowledge of Kubernetes architecture and operations in a large-scale environment.
- Strong scripting and automation skills (e.g., Python, Go, Bash).
- Experience with CI/CD systems (e.g., GitLab CI, Jenkins, ArgoCD) and building developer tooling.