Senior Deep Learning Performance Software Engineer
NVIDIAJob Overview
We are seeking a Senior Deep Learning Performance Software Engineer to join our team at NVIDIA, a leader in accelerated computing and AI technologies. This role is crucial for optimizing deep learning training, inference, and NVIDIA AI Services to enhance performance across all layers of the hardware/software stack.
Responsibilities
- Implement deep learning models across various data domains such as CV, NLP/LLMs, ASR, TTS, RecSys in multiple deep learning frameworks (PyTorch, JAX, TensorFlow 2, DGL, etc.).
- Develop and test new software features like Graph Compilation and reduced precision training, leveraging the latest hardware functionalities.
- Analyze, profile, and optimize deep learning workloads on state-of-the-art hardware and software platforms.
- Collaborate with researchers and engineers across NVIDIA to improve workload design, usability, and performance.
- Lead best practices for building, testing, and releasing deep learning software.
Qualifications
- 5+ years of experience in deep learning model implementation and software development.
- Bachelor's, Master's, or PhD degree in Computer Science, Computer Architecture, Mathematics, Physics, or a related technical field.
- Proficient in Python programming and knowledgeable in at least one deep learning framework.
- Strong problem-solving and analytical skills.
Preferred Skills
- Experience in performance measurements and profiling.
- Familiarity with running large-scale workloads in HPC clusters.
- Knowledge of DevOps/MLOps practices for deep learning-based product development.
- Understanding of Linux environments and containerization technologies like Docker.
- GPU programming experience (CUDA or OpenCL) is a plus.
Why NVIDIA?
Join a company that is at the forefront of the AI revolution, with some of the most brilliant minds in the technology world. We value diversity and are committed to creating an inclusive environment for all employees. This is an opportunity to work on powerful, enterprise-grade GPU clusters and impact the hardware and software roadmap in a significant way.
Benefits Extracted with AI
- Remote work flexibility
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