GPU/异构计算硬件选型与应用工程师
Core
Formulating roadmaps, evaluating, and integrating GPU/heterogeneous computing (FPGA/ASIC) components; optimizing performance for ML/AI workloads; tuning server stability and diagnosing data center faults.
Role type
Senior IC GPU/Heterogeneous Computing Hardware Selection and Application Engineer
Builds
GPU/AI servers and platforms for machine learning and AI business applications
Domain
Hardware engineering, AI infrastructure, Data Center operations
Deliverable
production ML models
Required skills
GPU/AI platform architecture, performance analysis, performance tuning, system architecture, GPU/AI SoC, interconnect structures, memory subsystems, GPU Direct RDMA, virtualization, deep learning architectures, distributed systems
Preferred skills
Expertise in GPU/AI SoC or platform architecture, interconnect structures, memory subsystems, GPU Direct RDMA, virtualization, deep learning architectures, or distributed systems
Responsibilities
Develop roadmaps for GPU/heterogeneous computing component selection and delivery; Optimize GPU/heterogeneous computing models for ML/AI business adaptation and performance; Evaluate and tune performance and stability of GPU/heterogeneous computing servers; Monitor, diagnose, and resolve GPU/heterogeneous computing faults in data centers; Collaborate with industry alliances and standard committees on emerging technology research and standard customization