Senior Software Architect, AI Networking
Tasks
- Author design documents and internal specifications
- Collaborate with model systems compiler and networking teams
- Contribute to open source efforts
- Design scalable multi-node LLM inference architectures
- Develop inference infrastructure to optimize latency throughput and cost efficiency
- Evaluate and integrate software and hardware technologies for model inference
- Prototype KV cache handling approaches
- Prototype dynamic batching
- Prototype tensor parallel pipeline parallel execution
- Translate architecture into reliable high-performance systems
Perks/Benefits
- N/A
Skills/Tech-stack
C++ | CUDA | Cluster scheduling | Compute scheduling | Deep learning | Distributed Systems | Dynamic batching | GPU Acceleration | Inter-node communication | KV cache | LLM Inference | Memory Orchestration | Networking | Performance optimization | Pipeline parallelism | Python | System Performance | System Performance Optimization | Tensor Parallelism
Education
Roles
AI | AI Systems Architect | Architect | Software Architect | Systems Architect
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