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Senior Software Engineer - Ai
Company | NVIDIA |
Address | Santa Clara, CA, United States |
Employment type | FULL_TIME |
Salary | |
Category | Computer Hardware Manufacturing,Software Development,Computers and Electronics Manufacturing |
Expires | 2023-08-25 |
Posted at | 9 months ago |
NVIDIA is seeking software engineers for its Deep Learning Algorithms team to develop and commercialize Artificial Intelligence solutions to diverse real-world problems related to Generative AI (Large Language Models, Multimodal), NLP, CV, Speech, Text, Recommendation Systems, Graph Neural Networks (GNN) etc.
- Research, prototype and develop effective tools and infrastructure pipelines
- Work at the intersection of deep learning applications, libraries, frameworks, and the entire software stack.
- Analyze, influence and improve deep learning libraries, frameworks and APIs according to good engineering practices
- Tackle end to end AI training and inference-deployment problems (data fetching, pre-processing, orchestrating the training runs, model serving)
- Collaborate with team members and other teams
- Expertise in standard software engineering methodology, e.g. design patterns, data structure and algorithms, unit testing, test automation, continuous integration, code reviews, design documentation, debugging/profiling and version control
- Strong analytical skill, Good communication, Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very complex projects.
- Strong knowledge of deep learning fundamentals and techniques.
- An MS and at least 3+ years of relevant industry experience in software development or a BS (or equivalent experience) and 5+ years of experience.
- Excellent Python and C/C++ programming knowledge
- Hands-on experience with one of the deep learning frameworks (e.g. JAX, PyTorch, TensorFlow, Keras, MxNet), or deep neural networks inference and deployment environments would be an asset (e.g. TRT, ONNX, Triton)
- Experience with cloud computing (e.g. end-to-end pipelines for AI training and inference on CSP (AWS/Azure/GCP))
- Prior background working at the intersection of deep learning applications, libraries, frameworks and the software stack.
- Relevant working experience with Docker and Kubernetes is a big plus.
- Prior experience with large scale AI training and understanding of the compute system concepts (latency/throughput bottlenecks, pipelining, multiprocessing etc)
- Knowledge of CPU and/or GPU architecture
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