NVIDIA is looking to redefine digital biology through the use of AI and sophisticated computing technology, requiring the implementation and product development of deep learning algorithms for life sciences applications.
Requirements
- Proficiency in Python and deep learning frameworks, especially PyTorch.
- Proficient knowledge in deep learning principles and HPC techniques.
- Familiarity with cloud-native technologies (e.g., Kubernetes, containers, microservices).
- Hands-on experience with large language models and distributed training/inference.
- Expertise in CUDA, TensorRT, and cuDNN.
- Experience building and deploying cloud-native AI applications.
Responsibilities
- Implement brand new biological foundation models as NVIDIA NIM Microservices (NIM).
- Compose and build agentic AI solutions for biological applications.
- Lead the development and productization of large-scale AI algorithms.
- Own major software features from development to deployment.
- Collaborate closely with applied research, AI infrastructure, and full-stack engineering teams to deliver robust, scalable solutions.
Other
- 8+ years of experience in AI/ML, with a strong focus on deep learning.
- BS/MS or equivalent experience in Computer Science, Physics, Mathematics, Statistics, or a related quantitative field.
- Shown technical leadership and ability to work independently and collaboratively.
- Strong communication abilities and a proven track record of multi-functional partnership.
- creative and autonomous engineer with a real passion for technology
