Systems Architect AI/ML Infrastructure
Core
Design end-to-end infrastructure architecture for AI/ML workloads including production inference and large-scale model training across multi-cloud and bare metal environments.
Role type
Senior Systems Architect (AI/ML Infrastructure)
Builds
Compute, storage, and networking systems for real-time voice AI inference and distributed ML training
Domain
Cloud Infrastructure / AI/ML Systems
Deliverable
infrastructure
Required skills
multi-cloud architecture design, GPU cluster design and management, Kubernetes compute orchestration, large-scale storage system design, capacity planning, FinOps/cost optimization, networking fundamentals
Preferred skills
architecting infrastructure for ML training workloads
Technologies
Kubernetes, AWS, bare metal, GPUs
Responsibilities
Define end-to-end infrastructure architecture for AI/ML workloads; Design multi-cloud and hybrid infrastructure strategies; Architect compute orchestration systems for GPU and CPU workloads; Design storage architectures for massive datasets; Lead capacity planning and infrastructure scaling; Drive cost optimization and FinOps practices; Establish architectural standards and design review processes
Seniority
Senior, hands-on IC with strategic scope