Senior ML Systems Engineer

Strong experience with ML pipeline orchestration (Kubeflow, MLflow, or similar platforms) Expertise in ML production systems (model serving, versioning, monitoring, CI/CD for ML) Experience with distributed training (multi-GPU, multi-node) and hardware acceleration (CUDA, TensorRT, or similar) Familiarity with cloud platforms (AWS, GCP, or Azure) for compute, storage, and ML services Strong communication and collaboration skills

Build and maintain ML training and inference infrastructure Implement automated model deployment and monitoring systems Optimize model serving for low-latency PCB layout generation Scale training infrastructure for large geometric datasets Ensure reliability and performance of production ML systems