Senior Compute Infrastructure Engineer

🔥 8 minutes ago

🌐 Israel, United States – Remote

🇮🇱 Israel – Remote 🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

👷 Infrastructure Engineer

👻 Ghost score 15%

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StackYak

WebsiteLinkedInAll Job Openings

2 - 10 employees

🤖 Artificial Intelligence

☁️ SaaS

🤝 B2B

Artificial Intelligence • SaaS • B2B

StackYak is an AI infrastructure orchestration platform that combines inference, GPU compute, and private networking into a single control plane. It provides hosted inference and dedicated GPU capacity, built-in private connectivity, and observability so teams can move models from testing to production without stitching together separate vendors. The platform targets developers, enterprises, and MSPs/resellers, and plans to add storage and security layers in future releases.

📋 Description

• Build the systems layer beneath StackYak’s AI infrastructure product • Decide what GPU capacity to own versus rent and where to standardize • Manage Linux, kernel, firmware, drivers, CUDA and/or ROCm across machines • Own decisions and boundaries between bare metal, VMs, and containers • Design and implement customer and workload isolation • Automate provisioning, rebuilding, recovery, and serving of machines • Integrate neoclouds and other compute providers • Specify hardware and coordinate its path from purchase order to booting machine through vendors, data-center partners, and remote hands • Diagnose failures across hardware, firmware, OS, virtualization, storage, network, and workload layers • Make the fleet operable by other people rather than relying on one-off machine knowledge • Turn heterogeneous owned and rented GPU capacity into trusted, operable production infrastructure • Participate in technical decisions and share production and on-call responsibility • Move between system design, implementation, debugging, and operations

🎯 Requirements

• Run production Linux at a depth where the answer was in the kernel, not in the docs • Operated GPU infrastructure for AI, HPC, cloud, or similarly demanding workloads • Carried NVIDIA and/or AMD platforms through a driver or firmware upgrade that did not go smoothly • Provisioned bare metal at a count where configuring machines by hand stopped being an option • Managed machines you could not physically reach, and recovered one anyway • Chosen between bare metal, KVM, and containers with a real consequence attached, and been able to say why • Written Terraform and Python that other people depend on in production • Hardened hosts and isolated workloads for customers who were not permitted to see each other • Debugged failures spanning hardware, firmware, OS, driver, network, or workload • Built or operated infrastructure at a neocloud, hyperscaler, GPU cloud, HPC environment, hosting company, data-center operator, or AI infrastructure company • Operated fleets mixing owned hardware with rented capacity • Worked with multi-GPU and multi-node systems • Understanding of NUMA, PCIe topology, RDMA, NIC placement, and physical topology • Specified or accepted hardware and understood the process from purchase order to booting machine • Designed infrastructure to safely serve multiple customers • Experience outside tightly siloed enterprise teams • Ability to work across design, implementation, debugging, and operations • No specific degree, certification, or academic credential required

🏖️ Benefits

• Meaningful equity • Remote and distributed work across time zones • Direct access to founders • Participation in technical decisions • Shared responsibility for production and on-call • Compensation structure determined based on location, engagement model, and experience • Flexible employment or contract engagement depending on location

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