What you will be doing:
In this position, you will research and develop techniques to GPU accelerate workloads in deep learning, machine learning or other AI domains.
Work directly with other technical experts in their fields (industry and academia) to perform in-depth analysis and optimization of complex AI and HPC algorithms to ensure optimal AI solutions on modern CPU and GPU architectures.
Publish and/or present discovered optimization techniques in developer blogs or relevant conferences to engage and educate the developer community.
Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools for our teams.
What we need to see:
An advanced degree in Computer Science, Computer Engineering, or related computationally focused science degree (or equivalent experience).
You have 8+ years of relevant experience in software development or research work.
Programming fluency in C/C++ with a deep understanding of algorithms and software development.
A background that includes parallel programming, e.g., CUDA, OpenACC, OpenMP, MPI, pthreads, etc.
Hands on experience doing low-level performance optimizations.
In-depth expertise with CPU and GPU architecture fundamentals.
Effective communication and organization skills, with a logical approach to problem solving, good time management, and prioritization skills.
Ways to stand out from the crowd:
Expertise in parallelization and performance optimization of Deep Learning models arising from Natural Language Processing, Computer Vision, Recommender Systems, etc.
Excellent understanding of linear algebra.
