Principal Engineer, Distributed Machine Learning

NVIDIA, the world leader in accelerated computing, is seeking a Principal Engineer to join their Distributed Machine Learning team. This role focuses on GPU-accelerated Apache Spark and distributed machine learning solutions, combining cutting-edge technology with practical business applications.

The position offers an opportunity to work on significant challenges in distributed ML/DL, making these technologies more accessible and efficient. You'll be at the forefront of developing GPU-accelerated distributed machine learning solutions, working with open-source communities, and improving existing frameworks like XGBoost, RAPIDS cuML, PyTorch, and TensorFlow.

As a Principal Engineer, you'll lead the design and development of new APIs and libraries, optimize performance for distributed training and inference, and contribute to major open-source projects. The role requires extensive experience in distributed systems, machine learning, and software development, with particular emphasis on technologies like Apache Spark, Kubernetes, and GPU computing.

The position offers a competitive compensation package, including a substantial base salary range of $272,000 - $425,500, plus equity. You'll be working with some of the most talented professionals in the technology industry, in an environment that values creativity and autonomy.

NVIDIA's commitment to fostering a diverse work environment and their position at the forefront of AI and accelerated computing make this an exceptional opportunity for a seasoned professional looking to make a significant impact in the field of distributed machine learning.