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Senior Software Architect, AI Systems and GPU Networking
On-siteFull-timeSoftware ArchitectureComputer Hardware
Join an AI networking research team developing architecture and software for accelerated AI data centers. The role combines hands-on technical design, research, hardware co-design, and proof-of-concept development across distributed AI, networking, storage, virtualization, and high-performance-com.
Responsibilities
- Enhance GPU networking technologies for AI workloads.
- Co-design GPU, DPU, and interconnect hardware features that accelerate data movement and enable inference and model-serving capabilities.
- Evaluate emerging technologies and partner relationships against technical and business goals.
- Lead the architecture and design of runtime systems, communication libraries, and AI-focused technologies.
- Lead proof-of-concept development to evaluate and advance new technologies.
Requirements
- Master’s or doctoral degree in computer science, electrical engineering, computer engineering, or equivalent experience.
- At least 5 years of industry experience in system architecture, AI systems architecture, AI scaling, AI framework parallelism, or deep learning training workloads.
- Experience with algorithm design, system programming, computer architecture, and operating systems.
- Experience with virtualization, networking, and storage.
- Strong understanding of performance profiling, optimization, and hardware feature definition and use.
- Strong programming and software development skills.
- Ability to communicate and collaborate effectively across multinational, multi-time-zone teams.
Nice to have
- Research track record.
- Experience with CPU, GPU, memory, storage, or networking architecture.
- Knowledge of deep learning frameworks and AI communication libraries such as NCCL, UCX, or MPI.
- Understanding of inference and training workloads, including prefill/decode and data or tensor parallelism.
- Strong communication skills and the ability to work autonomously.