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Platform Engineer - AI/ML Infrastructure (Kubernetes & Terraform)

Deepgram· Engineering
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Remote$136k - $240kFull-timePosted 7mo ago

About the role

Platform Engineer to build and operate hybrid AI/ML infrastructure spanning AWS and on-prem, focusing on Kubernetes, Terraform, and GPU workload orchestration with Slurm in a remote U.S. setting.

Responsibilities

  • Architect and maintain core computing platform using Kubernetes on AWS and on-premise
  • Develop and manage infrastructure with Terraform (IaC)
  • Design, build, and optimize AI/ML job scheduling and orchestration systems, integrating Slurm with Kubernetes
  • Provision, manage, and maintain on-premise bare metal server infrastructure for GPU computing
  • Implement and manage networking (CNI, service mesh) and storage (CSI, S3) for hybrid environments
  • Develop observability stack (monitoring, logging, tracing) and automation for operations, incident response, and performance tuning
  • Collaborate with AI researchers and ML engineers to build tools and workflows
  • Automate the life cycle of single-tenant, managed deployments

Qualifications

  • 5+ years of experience in Platform Engineering, DevOps, or SRE
  • Hands-on experience building and managing production infrastructure with Terraform
  • Expert-level knowledge of Kubernetes architecture and operations in large-scale environments
  • Strong scripting and automation skills (Python, Go, Bash)
  • Experience with CI/CD systems (GitLab CI, Jenkins, ArgoCD) and building developer tooling

Skills

Required:KubernetesTerraformPythonBash
Nice to have:SlurmGo

Benefits

  • Offers Equity
  • Offers Bonus
Last updated Sep 30, 2026. Interested? Apply on the company site.
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About Deepgram

Building foundational AI for speech transcription and understanding.

Deepgram is a foundational AI company on a mission to understand human language. We give any developer access to the most advanced speech AI transcription and understanding with just an API call. Our models deliver the fastest, most accurate transcription alongside contextual features like summarization, sentiment analysis, and topic detection. Beyond that, developers can: 🔊 Process live-streaming or pre-recorded audio 🌎 Transcribe in dozens of languages ⚙️ Train custom models for unique use cases 🔑 Access deep NLU with a unified API 💻 Build in any programming language with our SDKs ✅ Deploy on-prem or on DG’s managed cloud 📈 Get scalable GPU infra for training and inference Deepgram is a proud NVIDIA partner and Y Combinator company, and we recently completed a $72M Series B to define the future of AI Speech Understanding, making us the most-funded speech AI company at its stage.

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