AI/ML Infrastructure Architect

New

Skills

AI/ML Infrastructure Design Capacity Planning Container Orchestration Cost Optimization CPU Compute Management GPU Compute Orchestration Hybrid Cloud Architecture Low-Latency Serving Techniques Multi-Cloud Solutions Storage Solutions for Large Datasets

We are seeking a Systems Architect to define and design the end-to-end infrastructure for AI and ML workloads, including both production and training environments. This role involves creating multi-cloud and hybrid infrastructures that balance performance, reliability, cost, and vendor flexibility.

Key Responsibilities
  • Architect compute orchestration for GPU and CPU workloads.
  • Design storage solutions for large datasets and low-latency serving.
  • Lead capacity planning and scale ahead of demand.
  • Drive cost optimization and FinOps practices.
  • Think in systems, connecting compute, storage, and network.
  • Work across bare metal, cloud, and container orchestration.
  • Build cost-effective, burstable infrastructure for AI research.
  • Operate at a strategic level while maintaining technical depth.
Required Skills & Qualifications
  • Experience with real-time production and large-scale ML training.
  • Understanding of trade-offs among cost, performance, reliability, and velocity.
  • Strong knowledge of multi-cloud and hybrid infrastructure design.
  • Proficiency in compute orchestration for both GPU and CPU workloads.
  • Experience with storage solutions for low-latency serving.
  • Ability to conduct capacity planning and forecasting.
  • Familiarity with cost optimization techniques and FinOps practices.
  • Hands-on experience with bare metal, cloud, and container technologies.

No forms. Your profile is generated instantly.

Job Type: Remote

Salary: Not Disclosed

Experience: Entry

Duration: Months

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