GPU/异构计算硬件选型与应用工程师-Data（深圳）
Core
Formulating roadmaps, evaluating, and integrating GPU/heterogeneous computing (FPGA/ASIC) components for machine learning and AI business adaptation and performance tuning.
Role type
Senior IC GPU/heterogeneous computing hardware selection and application engineer
Builds
GPU/heterogeneous computing servers and AI platforms
Domain
Hardware engineering + Machine Learning/AI infrastructure
Deliverable
production ML models
Required skills
GPU/AI platform architecture design, performance analysis, performance tuning, system architecture (GPU/AI SoC, interconnect, memory subsystem, GPU Direct RDMA), GPU/AI virtualization, deep learning architecture, distributed systems
Preferred skills
GPU/AI platform architecture, performance analysis, performance tuning, system architecture (GPU/AI SoC, interconnect, memory subsystem, GPU Direct RDMA), GPU/AI virtualization, deep learning architecture, distributed systems
Responsibilities
Formulating roadmaps for GPU/heterogeneous computing component selection, evaluating and integrating new components, adapting and tuning GPU/heterogeneous computing for ML/AI workloads, evaluating and tuning server performance and stability, monitoring and diagnosing GPU/heterogeneous computing faults in data centers, collaborating on emerging technology research and standard customization
Seniority
Senior, hands-on IC