AI Infrastructure Architect
Role details
Job location
Tech stack
Requirements
Do you have experience in Technical writing?, Architect MaxtaOS core systems: GPU resource management, multi-tenant scheduling, hardware abstraction layer Design MaxModel registry and deployment pipeline: model packaging, version control, A/B testing infrastructure Lead integration with edge computing platforms (Jetson, custom CUDA kernels) Define API contracts and system boundaries across the MaxtaOS + MaxModel stack Mentor engineering team on distributed systems best practices Requirements 8+ years in distributed systems, infrastructure, or platform engineering Deep expertise in GPU computing (CUDA, multi-GPU scheduling, heterogeneous hardware) Production experience with Kubernetes, container orchestration, or custom scheduling systems Strong background in Python, Go, or C++ for systems programming Experience with ML model serving (TorchServe, Triton, vLLM, or similar) Familiarity with edge computing platforms (NVIDIA Jetson, ARM64 deployment) Excellent system design and technical documentation skills
Benefits & conditions
Pulled from the full job description
- 401(k) matching
- Vision insurance, Competitive salary + equity in a pre-IPO AI infrastructure company Work directly with the CEO on cutting-edge AI systems Backed by Andreessen Horowitz and Intel Capital 100+ patents portfolio - real deep-tech, not wrapper products Flexible hybrid work model (Silicon Valley + remote) Health, dental, vision + 401K matching Conference budget + continuous learning