Nvidia AI Algorithm Software Engineer 

Taiwan, Taiwan Province, Hsinchu 

874589684

This challenging role will require someone who deeply understands and can architect algorithms with Large Language and Multi-modal (LLM/LMM) Foundation models to advance the application of artificial intelligence and machine learning to the Manufacturing AI market. Practical experience in the use and the building of Computer Vision algorithms, models and tools will be critical.

What You’ll Be Doing :

• Architect, analyze, develop, and prototype key deep learning algorithms and solutions as a core member of our growing software team.

• Collaborate with diverse software, research, and hardware teams across geographies to analyze the interplay of hardware and software architectures solve critical problems and future applications

• Support engagements with customers and their third-party software providers. Collaborate with Product Management, Marketing, and Developer Technology teams.

• Develop algorithms (such as zero/few-shot learning, unsupervised learning) to address data scarcity and collection challenges.

• Utilize generative models (Diffusion, GANs, VAEs) for data generation to overcome data scarcity issues.

What We Need To See :

• MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field with a focus on Deep Learning, Machine Learning, and Computer Vision with 2+ years of work experience.

• Proven experience in algorithm development for data analytics, especially with LLMs and Multi-Modal Foundation models. Experience working and curation with multi-modal datasets.

• Experience with algorithms including zero/few-shot learning, self-supervised and unsupervised learning techniques, generative AI models for synthetic dataset

• Proficiency in working with deep learning frameworks such as TensorFlow and PyTorch, Strong programming skills in Python and/or C++

• Strong communication skills and ability to work in a collaborative environment.

Ways To Stand Out From The Crowd :

• Track record of contributions to academic publications in the field of AI/ML or open-source projects.