Used Tools & Technologies
Not specified
Required Skills & Competences ?
Python @ 6 Algorithms @ 4 Machine Learning @ 4 PyTorch @ 4 CUDA @ 4 GPU @ 4Details
NVIDIA is seeking a Deep Learning Computer Architect to design hardware accelerator and processor architectures that enable state-of-the-art machine learning and data analytics algorithms and applications on next-generation mobile, embedded, and datacenter platforms.
Responsibilities
- Contribute to features that help next-generation GPUs advance the state of AI.
- Keep up with the latest deep learning (DL) research.
- Collaborate with diverse teams including DL researchers, hardware architects, and software engineers.
- Analyze the behavior of various deep learning methods.
- Propose new features to accelerate or enable various DL methods.
- Study the benefits of the proposed features.
Requirements
- MS or PhD degree in computer science, computer architecture, electrical engineering, or related field, or equivalent experience.
- 5+ years of relevant experience in areas including computer architecture, performance analysis and optimization, and deep learning workloads with performance tuning considerations such as parallelization and fusion strategies.
- Experience with core deep learning kernels such as matrix multiply and convolution.
- Programming fluency in C++ and ideally Python.
- Experience with GPU computing (CUDA).
- Experience with deep learning frameworks like PyTorch.
Benefits
- Competitive base salary ranging from 184,000 USD to 425,500 USD, determined by location, experience, and peer pay.
- Eligibility for equity and additional benefits.
- Opportunity to work at a forward-thinking technology company with a focus on AI and intelligent machines.
- Commitment to diversity and equal opportunity employment.