4 months ago

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

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 hours agoStatus: Live

Job Summary

Experienced Site Reliability Engineer to build and operate a hybrid infrastructure foundation for AI/ML research and product development. You’ll architect and run Kubernetes on AWS and on-premises, manage IaC with Terraform, optimize GPU workloads with Slurm, and oversee bare-metal servers, networking, storage, and observability to enable scalable, low-latency AI workflows across cloud and data center environments.

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Seniority: Sr. Manager level

Key Responsibilities

•Architect and maintain our core computing platform using Kubernetes on AWS and on-premise, providing a stable, scalable environment for all applications and services.
•Develop and manage our entire infrastructure using Infrastructure-as-Code (IaC) principles with Terraform, ensuring our environments are reproducible, versioned, and automated.
•Design, build, and optimize our AI/ML job scheduling and orchestration systems, integrating Slurm with our Kubernetes clusters to efficiently manage GPU resources.
•Provision, manage, and maintain our on-premise bare metal server infrastructure for high-performance GPU computing.
•Implement and manage the platform's networking (CNI, service mesh) and storage (CSI, S3) solutions to support high-throughput, low-latency workloads across hybrid environments.

Pay and Benefits

Salary: USD 150,000 - 220,000 annually

Equity and Bonus:Equity

Perks:Paid Leave401kLearning StipendHome OfficeWellness Stipend

Key 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.
•Experience with high-performance compute (HPC) job schedulers, specifically Slurm, for managing GPU-intensive AI workloads.
•Experience managing bare metal infrastructure, including server provisioning (e.g., PXE boot, MAAS), configuration, and lifecycle management.

Experience:5+ yearsAI/MLCloudDevops

Skills:KubernetesTerraformSlurmPXEMAASPythonGoBashGitLab CIJenkinsArgoCDCalicoCiliumCephRookSRE

Tech Stack:KubernetesAWSTerraformSlurmPXEMAASPythonGoBashGitLab CIJenkinsArgoCDCalicoCiliumCephRookKubernetes NetworkingCSIS3

Company Brief

Deepgram

Deepgram builds a real-time Voice AI platform delivering speech-to-text, text-to-speech, and voice-agent APIs for developers and enterprises, focusing on low-latency, high-accuracy voice models and scalable deployment options.

Industry: API Platforms

Company Size: Medium (51 to 250 employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series C

Headquarters: San Francisco, United States

Founded: 2015

Glassdoor: 4.5

Website LinkedIn Glassdoor

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Deepgram

4 months ago

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

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 hours agoStatus: Live

Job Summary

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Seniority: Sr. Manager level

Key Responsibilities

•Architect and maintain our core computing platform using Kubernetes on AWS and on-premise, providing a stable, scalable environment for all applications and services.
•Develop and manage our entire infrastructure using Infrastructure-as-Code (IaC) principles with Terraform, ensuring our environments are reproducible, versioned, and automated.
•Design, build, and optimize our AI/ML job scheduling and orchestration systems, integrating Slurm with our Kubernetes clusters to efficiently manage GPU resources.
•Provision, manage, and maintain our on-premise bare metal server infrastructure for high-performance GPU computing.
•Implement and manage the platform's networking (CNI, service mesh) and storage (CSI, S3) solutions to support high-throughput, low-latency workloads across hybrid environments.

Pay and Benefits

Salary: USD 150,000 - 220,000 annually

Equity and Bonus:Equity

Perks:Paid Leave401kLearning StipendHome OfficeWellness Stipend

Key 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.
•Experience with high-performance compute (HPC) job schedulers, specifically Slurm, for managing GPU-intensive AI workloads.
•Experience managing bare metal infrastructure, including server provisioning (e.g., PXE boot, MAAS), configuration, and lifecycle management.

Experience:5+ yearsAI/MLCloudDevops

Skills:KubernetesTerraformSlurmPXEMAASPythonGoBashGitLab CIJenkinsArgoCDCalicoCiliumCephRookSRE

Tech Stack:KubernetesAWSTerraformSlurmPXEMAASPythonGoBashGitLab CIJenkinsArgoCDCalicoCiliumCephRookKubernetes NetworkingCSIS3

Company Brief

Deepgram

Industry: API Platforms

Company Size: Medium (51 to 250 employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series C

Headquarters: San Francisco, United States

Founded: 2015

Glassdoor: 4.5

Website LinkedIn Glassdoor