Senior Software Engineer
Develop and prototype distributed training and inference solutions, optimizing AI networking across communication, transport, and network layers for large-scale computing systems.
Responsibilities
- Prototype end-to-end solutions for distributed training and disaggregated inference performance
- Analyze and optimize communication flows across application, transport, and network layers
- Develop system software spanning communication libraries, drivers, and firmware integrations
- Collaborate with hardware, firmware, and SDK teams to co-design network features
- Validate and integrate prototypes into AI infrastructure and products
Requirements
- BSc, MSc, or PhD in Computer Science or Electrical Engineering
- At least 5 years of relevant experience or equivalent knowledge
- Deep understanding of networking and communication internals, including NCCL, RDMA/RoCE, and congestion control
- Hands-on experience with hardware, software, and firmware integration
- Low-level programming experience with C/C++, kernels, or drivers
- Background in distributed training systems such as PyTorch DDP, Megatron-LM, or DeepSpeed
Nice to have
- Experience with programmable data planes such as P4, eBPF, DOCA SDK, or switch SDKs
- Familiarity with NIC firmware scheduling, in-network computing, or congestion management
- Contributions to open-source projects, academic papers, or performance benchmarking tools
- Background in AI factory architectures, distributed inference, or network telemetry
- Experience turning prototypes into product features and demonstrating technical leadership