
GPU Architect
4 days ago
As a seasoned architect, you will lead the design and implementation of groundbreaking GPU computers that run demanding deep learning, high-performance computing, and computationally intensive workloads.
Key responsibilities include:
- Designing and implementing GPU computers that run complex workloads.
- Identifying architectural changes and/or new approaches for accelerating deep learning models.
- Collaborating with various teams to drive an end-to-end workflow from data curation and training to performance optimization and deployment.
Requirements:
- Master's or PhD in Computer Science, Electrical Engineering, or related field.
- 7+ years of experience in machine learning, numerical analysis, performance analysis, model compression and optimization, and computer architecture.
- Expertise in C/C++ programming, PyTorch, TensorRT, CuDNN, and GPU computing (CUDA, OpenCL, OpenACC).
- Hands-on experience with container technologies like Docker, Singularity, Shifter, Charliecloud.
- Proficient in Python programming and bash scripting.
- Excellent communication and collaboration skills.
Preferred qualifications:
- Hands-on experience with HPC cluster job schedulers such as Kubernetes, SLURM, LSF.
- Familiarity with cloud computing architectures.
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