Principal Deep Learning Communication Architect
Core
Define long-term technical roadmaps and design next-generation communication primitives for scaling AI models across massive clusters.
Role type
Principal Deep Learning Communication Architect
Builds
Communication libraries (NCCL, NVSHMEM, UCC) and collective algorithms for trillion-parameter LLMs and Agentic AI.
Domain
High-performance computing (HPC) and distributed deep learning
Deliverable
production ML models
Required skills
3D parallelism (Data, Tensor, Pipeline, Context, Expert, ZeRO), RDMA/RoCE/InfiniBand verbs, GPU memory hierarchy (HBM3e/HBM4), CUDA programming, high-throughput inference engines (TensorRT-LLM, vLLM, SGLang)
Preferred skills
Framework development (Megatron-Core, DeepSpeed, JAX/XLA), upstream open-source contributions, rack-scale system deployment, patents/papers in systems/architecture venues
Technologies
NVLink, Spectrum-X, Quantum-X, NCCL, UCX, UCC, NVSHMEM, MPI, TensorRT-LLM, vLLM, SGLang, CUDA
Responsibilities
Define technical roadmaps for communication libraries, optimize collective algorithms for heterogeneous interconnects, co-design communication primitives with application developers, collaborate with silicon architects on hardware specifications, develop analytical models to predict system behavior
Seniority
Principal, hands-on IC with strategy & mentorship
