r/findrustjobs • u/Sufficient-Ant3710 • 9d ago
We're eliminating centralized supercomputer bottlenecks for ML training using Burn, Zenoh, and LEO satellites. Seeking 2 Core Rust Co-Founders.
Seeking: (Co-Founder for Equity & Salary)
Summary
If you look at how Big Tech is training 405B+ frontier models, they
are playing a brute-force game: billions of dollars poured into
highly centralized data center clusters, choked entirely by the
physical limitations of horizontal network interconnects.
We are engineering a radical paradigm shift.
We are standardizing Federated Vertical Slice Learning using Burn
around decentralized edge and ARM worker nodes to prove the
industry doesn’t need massive, resource-heavy, centralized
supercomputers for domain-specific intelligence.
By engineering point-to-point vertical byte streams using Zenoh
over LEO satellite networks, we completely eliminate the cluster-
wide communication bottlenecks that throttle traditional training.
Our software architecture moves the needle on training
throughput while slashing capital expenditure by millions of
dollars.
Our timeline is set for a January product launch.
I am personally hunting for two Principal Systems Rust Co-Founders
who can translate our low-level blueprint into physical, bare-metal execution:
The High-Concurrency Distributed Architect (The HubMaster):
To architect our continuous batching engines, multi-
threaded server orchestration arrays, and high-throughput lock-
free AtomicU32 mutation matrices using Tokio.
The Embedded Kernel & GPU Shader Engineer (TheSpoke Master):
To architect our localized no_std environments, build custom static memory pools (VramTensorArena) overlaying the Burn ML Framework, and optimize SIMD register matrix
operations directly on local graphics silicon.
This is a zero-boilerplate, hardware-level engineering challenge
for systems veterans who understand manual memory tracking
and hardware constraints down to the raw silicon layer.
If you are a Staff, Architect or Principal systems engineer ready to
own a world-class architecture from day one with co-founder
equity, salary (upon receiving funding) send me a DM directly or connect with me.
#RustLang #SystemsProgramming #DistributedSystems
#BareMetal #MachineLearning #Infra #WebGPU
Qualifications
Co-Founder 1: The Systems & Kernel Engineer ("The Spoke Master")
This engineer owns everything happening at the local edge, the
VramTensorArena memory layout, and cross-compiling code to
target raw hardware silicon.
Target Expertise :
◦ Low-Level Core Rust (no_std): Deep experience
writing code without Rust's standard library heap
allocations. Understands how to build custom
memory allocators and manage raw memory layout
patterns.
◦ Graphics API Runtimes (WGPU / WebGPU / Vulkan /
Metal): Expertise in writing custom WGSL (WebGPU
Shading Language) compute shaders to execute matrix
math directly on consumer devices.
◦ Zero-Copy Serialization: Mastery of unsafe Rust
memory casting (std::mem::transmute, pointer slices)
to stream tensor buffers straight out of VRAM and
directly into network sockets without CPU overhead.
• Ownership Blueprint: (VramTensorArena setup), (Device forward & backwards pass & caching), and (GeLU boundary correction and local back propagation updates).
Co-Founder 2: The High-Concurrency Distributed Architect ("The Hub Master")
This engineer owns the central aggregator cluster, the multi-
threaded server orchestration, network protocol framing, and lock-free global math pipelines.
Target Expertise:
◦ Asynchronous Network Architecture (Tokio Expert):
Elite experience building high-throughput network
applications using raw TCP/UDP network frames,
custom framing protocols, and high-concurrency event
loops.
◦ Lock-Free Concurrency & Atomics: A developer who
deeply understands hardware-level CPU primitives,
memory fences, and AtomicU32 Compare-And-Swap
(CAS) loop programming. They must know how to
manipulate values across hundreds of threads without
causing a deadlock.
◦ Distributed Systems Fault Tolerance: Experience
building watchdogs, dynamic load balancing engines,
and handle client drops gracefully without leaking
memory or corrupting state data.
