MaaS 架构师
Tasks
- Apply prefix caching and paged attention
- Build LLM inference gateway
- Configure priority queues and multi tenant isolation
- Create unified inference load abstraction
- Deploy quantized models
- Design MaaS platform architecture
- Design token level metering
- Develop GPU elastic scaling strategy
- Enable continuous batching and speculative decoding
- Ensure model service SLAs latency throughput
- Implement KV cache aware scheduling
- Implement model routing and traffic scheduling
- Package inference services with observability
- Select and optimize inference engine frameworks
Perks/Benefits
- N/A
Skills/Tech-stack
Attention | Batching | C++ | CUDA | Continuous batching | GPU scheduling | Go | KV cache | Kubernetes | LLM serving | Multi-tenancy | NCCL | Paged Attention | Prefix caching | Python | Quantization | Ray Serve | SGLang | Speculative decoding | TensorRT-LLM | Triton | VLLM
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
Regions
Countries
States
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