The point where experts and best companies meet
Share
What you’ll be doing:
Evaluate performance bottlenecks and come up with ways to improve performance in the hypervisor environment for the GPU application stack
Generate consistent performance metrics based on industry standards and develop frameworks, needed scripts for collecting and reporting the metrics.
Work actively on creating micro benchmarks for performance evaluation in cloud and bare metal environment.
Work collaboratively with other specialists and be willing to tackle any engineering tasks that commit to the progress towards the goals of the team and the company.
What we need to see:
Advanced knowledge in Computer Architecture. Detailed knowledge of NUMA, Cache coherency, PCIe.
Deep understanding of performance evaluation and analysis in virtualized environment with at least one hypervisor.
Experience with tools for performance analysis.
Solid knowledge of Computer I/O (e.g., RDMA, remote storage, etc.)
Good knowledge of Linux kernel internals.
Strong coding skills in languages like python, C/C++.
Shell scripting experience. Python and Perl experience is a Plus.
Experience with version control tools (e.g. git).
Excellent communication skills.
Ability to work in dynamic environment and can-do attitude.
Bachelor of Science Degree in Electrical Engineering or Computer Science or equivalent experience.
6+ years of experience
Ways to stand out from the crowd:
Good understanding of ARM and x86 platforms at architecture level. Experience with GPU-accelerated software. Knowledge of deep learning neural networks, how they work and familiarity with various DL frameworks.
Experience with container technologies (e.g. Docker). Deep understanding of technology and passionate about what you do
Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic work environment.
You will also be eligible for equity and .
These jobs might be a good fit