Machine Learning Systems Engineer (MLSys)

Responsibilities

• System Development & Maintenance
  Contribute to the development, optimization, and maintenance of core components of the machine learning platform, including feature stores, experiment tracking systems, model registries, workflow orchestration, and serving frameworks
• Training Efficiency Optimization
  Assist in optimizing the performance of distributed training frameworks (e.g., PyTorch DDP, DeepSpeed, FSDP) on large-scale clusters, addressing challenges such as resource scheduling and communication bottlenecks
• Inference Performance Optimization
  Participate in model deployment and serving, including performance profiling and acceleration through model compilation (e.g., TVM, TensorRT), operator optimization, computation graph optimization, and batching strategies
• Infrastructure Support
  Leverage technologies such as containerization (Docker), orchestration (Kubernete...