About the Company
We are an early-stage, deeply technical startup building next-generation network acceleration infrastructure for AI/ML workloads and other mission-critical systems. Our focus is not application-layer AI — it’s chip-level, transport-layer, and systems-level performance engineering.
Our technology reduces GPU idle time during large-scale LLM training by optimizing communication across clusters. Beyond AI, we serve industries including mobility, satellite communications, aerospace, atmospheric optical systems, VPN/SD-WAN, and defense.
This is PhD-level, systems-heavy engineering. If your background is primarily high-level ML frameworks (e.g., PyTorch-only development), this is not the role. If you love transport protocols, congestion control, and performance tuning at the metal — you’ll fit right in.
What You’ll Do
- Design and implement high-throughput, low-latency transport systems
- TCP/QUIC/UDP
- Congestion control & pacing
- Flow control
- Advanced transport optimization
- Build production-grade services in:
- C / C++
- Rust
- Optimize end-to-end performance:
- CPU
- GPU
- I/O
- Interconnects
- Work at the networking acceleration layer for:
- AI/ML cluster communication
- Data center optimization
- Over-the-air acceleration (e.g., satellite, drone, remote systems)
- Collaborate directly with:
- Hyperscalers
- Chip manufacturers
- Large VPN and networking partners
- Ship real deployments into production environments.
What You Bring
Required:
- Strong proficiency in C/C++
- Rust experience or strong willingness to learn
- Deep understanding of:
- Networking transport protocols
- Congestion & flow control
- Systems-level architecture
- Strong mathematical foundation
- Demonstrated systems performance optimization experience
- Ability to troubleshoot without relying on AI-generated solutions
- Proven capability to operate in deeply technical environments
This role requires engineers who truly understand what’s happening under the hood — not just framework users.
Nice to Have
- GPU porting experience
- RDMA / RoCEv2 / Infiniband / NVLink knowledge
- FEC / erasure coding experience
- Mobile networking experience (Android/iOS)
- Experience optimizing data plane systems
- Experience working with distributed teams in performance-critical systems
Team & Stage
- Hiring 3–5 engineers:
- 1 GPU-level / hardware-focused engineer
- 2–3 senior networking systems engineers (this role)
- 1–2 junior/integration engineers
How We Hire
We move fast and value:
- Technical depth
- Direct communication
- No fluff
- No AI-regurgitated resumes
- Real systems knowledge
Why Join
- Work on the critical path of AI infrastructure
- Solve problems most engineers never get to touch
- Join a small, elite, senior-heavy team
- Direct exposure to top-tier enterprise partners
- Real ownership, real impact
Ideal Candidate Profile
You:
- Obsess over packet traces and performance counters
- Care about microseconds
- Have read congestion control papers for fun
- Can debug distributed systems without panic
- Prefer hard engineering problems over hype