Profile cover
D

AI Multi-Cloud Resource Abstraction Developer

David Dubois

Full-time · Job · Berlin

About the role

ML teams shouldn't need to know whether their training job runs on AWS p4d instances, GCP A2 VMs, or Azure NC-series machines. Our abstraction layer lets data scientists request "4 GPUs with 80GB memory for 8 hours" and we handle provider selection, instance provisioning, data staging, and cleanup. The ML engineer writes model code; we handle the cloud. The abstraction challenge is mapping a generic resource request to provider-specific APIs that behave differently, price differently, and fail differently. An A100 on AWS has different networking constraints than the same GPU on GCP. Spot availability varies by region and time of day. Storage mounting works differently on each platform. You'll build the translation layer that hides these differences behind a clean interface. The multi-cloud platform team is five engineers. You'll own the resource abstraction module for compute and storage, adding support for new instance types and providers as our clients request them.

Responsibilities

  • Build the resource abstraction layer mapping generic requests to cloud-specific APIs
  • Handle provider-specific differences in networking, storage, and GPU configuration
  • Implement intelligent provider selection based on availability, cost, and performance
  • Design fallback logic for when preferred resources are unavailable
  • Add support for new instance types and cloud providers
  • Monitor abstraction layer reliability across all supported providers

Requirements

  • 3+ years in cloud infrastructure with multi-cloud experience
  • Strong knowledge of AWS, GCP, and Azure compute and storage services
  • Experience with Kubernetes and container orchestration
  • Proficiency in Python for infrastructure automation
  • Understanding of GPU instance types and ML workload requirements

Benefits

  • Fully remote across EU time zones
  • 30 days PTO
  • €2,500 home office budget
  • Stock options
  • Work on multi-cloud infrastructure used by hundreds of ML teams

Keep exploring related roles

Use these topic pages to discover more roles in the same hiring cluster.

Categories

MLOps & AI Infrastructure Automation & AI Workflows

Skills

python docker kubernetes aws gcp

Related remote AI jobs

Nearby roles that share similar skills, categories, or hiring intent.

Browse all jobs

Senior Product Security Engineer

RemoteAI company

Full-time Senior

AI Resident UK/EMEA

RemoteAI company

Full-time

Devops Engineer, US

RemoteAI company

Full-time

Infrastructure Engineer

RemoteAI company

Full-time

partnerships

RemoteAI company

Full-time

Senior AI R&D Engineer – Model Training (f/m/d)

RemoteAI company

Full-time Senior

Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

MLOps & AI Infrastructure Automation & AI Workflows

Skills

python docker kubernetes aws gcp azure

Ready to apply for this role?

Create a free talent account in under 2 minutes.

  • Apply to verified AI companies
  • Get AI-matched job recommendations
  • Message hiring managers directly
  • Build your public AI talent profile
Create free account & apply Log in

Interested in this role? Create your free profile to apply.

Apply — create free profile