Description review
Thunder Compute (YC S24) | C++ Systems, Infrastructure, BizOps | San Francisco (Onsite) | Full-time
Thunder Compute (YC S24) · San Francisco (Onsite) · back to the listing
HR standards
43/100
poor
Title ↔ description
58/100
needs work
Reads as
Backend Engineer
98% confident
What this role officially is
software developer — ESCO, the EU occupation classification
Software developers implement or program all kinds of software systems based on specifications and designs by using programming languages, tools, and platforms.
Also known as: application developer, application programmer, solutions developer, programmer, software specialist, application software developer
How others title the same work
Large employers
- Software Engineer - OpenStack Canonical
- C, Golang Software Engineer working on dqlite, a Raft extension for SQLite Canonical Ltd.
- Containerization & Virtualisation Engineer Canonical Ltd.
- Go (Golang) Software Engineer, Developer Tooling and Containers Canonical Ltd.
- Golang Engineer Canonical Ltd.
Startups
- Anterior (Sequoia-backed, Series B) | Senior Member of Technical Staff | On-Site (New York, NY) | Full Time | $230,000–$300,000 + equity Anterior (Sequoia-backed, Series B)
- BitPay | Senior Backend Software Developer | Atlanta, GA | REMOTE (US) | BitPay
- Distributed Systems Engineer Beam
- Software Engineer, Platform Beam
- Blaine, WA | CaseLight Systems Inc. (CSI) | Solo Founder | Remote (US Only) | Founding Systems Engineer | FULL EQUITY (30% Stake) Blaine, WA
What the listing never says
- No section describes what the person would actually do. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
- No location or timezone policy stated, so a candidate cannot tell where they may work from. Scope clarity
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
We're building the VMware for GPUs. Most GPUs in the cloud sit idle a lot of the time because they're bolted to one machine over PCIe. We decouple them.
Our virtualization layer is a userspace shim, loaded through LD_PRELOAD, that intercepts CUDA calls and ships them over the network to a host with a physical GPU somewhere else in the data center. Workloads run unchanged. When a process goes idle, the GPU detaches and gets reassigned, and reattaches in tens of milliseconds when it's needed again. Think Ceph for GPUs: the GPU becomes a network resource a cluster-wide scheduler can pool and pack.
The hard part is making that fast. We're within ~10% of native on most AI workloads, and it lets us serve ~1.8x more users on the same fleet. We run it in production as our own GPU cloud and sell it to enterprises with underutilized fleets.
Team is from Citadel Securities, Aquatic, Old Mission, AWS, and Bain. Series A, $17.5M raised from Matrix and Y Combinator.
Open roles:
- Software Engineer, C++ Systems ($215K-$325K + meaningful equity). Low-level, latency-sensitive work on the virtualization layer. Quant dev / HFT background preferred: https://jobs.ashbyhq.com/thundercompute/2efae53b-817c-43e7-9da3-72694813f608
- Software Engineer, Infrastructure ($150K-$250K + meaningful equity). Go, Kubernetes, reliable systems at scale: https://jobs.ashbyhq.com/thundercompute/927a922b-c607-4b0e-a6f2-451571a537f4
- Business Operations Lead ($150K-$225K + meaningful equity): https://jobs.ashbyhq.com/thundercompute/4f28e418-b77b-446e-a30e-6b5bed36c093
If you're cracked at building systems software and want to do something more meaningful than creating liquidity, reach out.
Email me at [email protected] and mention HN. I read every email.
Our virtualization layer is a userspace shim, loaded through LD_PRELOAD, that intercepts CUDA calls and ships them over the network to a host with a physical GPU somewhere else in the data center. Workloads run unchanged. When a process goes idle, the GPU detaches and gets reassigned, and reattaches in tens of milliseconds when it's needed again. Think Ceph for GPUs: the GPU becomes a network resource a cluster-wide scheduler can pool and pack.
The hard part is making that fast. We're within ~10% of native on most AI workloads, and it lets us serve ~1.8x more users on the same fleet. We run it in production as our own GPU cloud and sell it to enterprises with underutilized fleets.
Team is from Citadel Securities, Aquatic, Old Mission, AWS, and Bain. Series A, $17.5M raised from Matrix and Y Combinator.
Open roles:
- Software Engineer, C++ Systems ($215K-$325K + meaningful equity). Low-level, latency-sensitive work on the virtualization layer. Quant dev / HFT background preferred: https://jobs.ashbyhq.com/thundercompute/2efae53b-817c-43e7-9da3-72694813f608
- Software Engineer, Infrastructure ($150K-$250K + meaningful equity). Go, Kubernetes, reliable systems at scale: https://jobs.ashbyhq.com/thundercompute/927a922b-c607-4b0e-a6f2-451571a537f4
- Business Operations Lead ($150K-$225K + meaningful equity): https://jobs.ashbyhq.com/thundercompute/4f28e418-b77b-446e-a30e-6b5bed36c093
If you're cracked at building systems software and want to do something more meaningful than creating liquidity, reach out.
Email me at [email protected] and mention HN. I read every email.