jobs in China Mobile International Limited

全职 LLM Inference Engineer 工作, 薪水, China Mobile International Limited Federal Territory 公司招聘中 - Ricebowl

KL City, Federal Territory

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工作地点

  • Kuala Lumpur Federal Territory Malaysia

职位描述

岗位职责

1. Deployment

  • Set up NVIDIA B300 GPU servers, including drivers, CUDA, NCCL, RDMA, Docker, and Kubernetes.
  • Deploy vLLM, SGLang, or TensorRT-LLM and build container images.
  • Convert, quantize, and shard open-source models for multi-node, multi-GPU inference.
  • Provide OpenAI-compatible APIs and integrate gateways, authentication, rate limits, quotas, and caching.

2. Performance Optimization

  • Optimize batching, KV cache, prefix cache, FP8, and distributed inference.
  • Improve throughput and reduce time to first token (TTFT).
  • Identify GPU, memory, network, and gateway bottlenecks.
  • Optimize 128K–256K long-context workloads.

3. Testing and Delivery

  • Test API functions, model quality, performance, capacity, and stability.
  • Validate streaming, tool calls, structured output, multimodal input, caching, error handling, and security.
  • Run benchmarks such as AIME 2026, GPQA Diamond, MMLU-Pro, and LongBench v2.
  • Analyze THVV reports, fix issues, and prepare final test reports.

4. Operations

  • Monitor GPU usage, memory, TPM/RPM, TTFT, success rates, errors, and cache hit rates.
  • Resolve OOM errors, GPU failures, rate-limit errors, timeouts, network issues, and service hangs.
  • Maintain at least 99.9% monthly SLA.
  • Run regular stress tests and regression tests.
  • Manage customer credits, quotas, and rate limits.

Requirements

  • Bachelor’s degree or above in Computer Science or a related field.
  • At least one year of experience in LLM inference deployment.
  • Experience with bare-metal GPU servers and Docker/Kubernetes.
  • Strong knowledge of vLLM, SGLang, or TensorRT-LLM.
  • Familiarity with CUDA, NCCL, RDMA/InfiniBand, KV cache, FP8, and distributed inference.
  • Good Python, Linux, and shell scripting skills.
  • Experience with THVV, EvalScope, or similar testing tools.
  • Familiarity with OpenAI-compatible APIs, streaming, tool calls, and structured output.


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