us to shape the performance analysis infrastructures for GPUs.We buildanalysis tools and visualization frameworks that empower engineers toGPU performance for Deep Learning and HPCthe next-gen GPUs architectures.
be doing:
Architect Performance Tooling: Develop infrastructure tools/libraries for GPU performance analysis, visualization, and automated workflows used across GPU SW/HW development life cycle.
Unlock Architectural Insights: Analyze GPU workloads toidentifybottlenecks and define new hardware profiling features that enhance perf debug and profiling capabilities.
AI-Powered Automation: Build AI/ML-driven tools to automate performance analysis, generate perf optimization guidance, and improve user experience of profiling infrastructure.
Cross-Stack Collaboration
What we need to see:
BS+ in Computer Science, Electronic Engineeringor related (or equivalent experience)
4+ years of software development
Strong software skill in design, coding (C++ and Python), analytical and debugging in low-level program
Strong grasp of computer architecture (pipelines, memory hierarchies) and operatingsystem fundamentals
Experience with performance modeling, architecture simulation, profiling, and analysis.
Self-starter who thrives in dynamic environments and manages competing priorities effectively.
Ways to stand out from the crowd:
Experience withbuildingperformance debugging and analysis toolson silicon and simulators. Experience of developing application snapshot and replay tool is a big plus.
Familiar withCUDASystem SoftwareStack(e.g.,CUDADriver/Runtime APIs), CUDA kernel optimization and understand GPU architecture
Familiarity with GPU performance profiling tools like Nsight System, Nsight Compute, NVTX, etc, or experience for developing similar tools for other processors.
Practical experience or projects demonstrating AI/ML-based code generation, automated data analysis, or workflow assistants.
משרות נוספות שיכולות לעניין אותך