Responsibilities

• Conduct innovative research to enhance the science and technology of machine learning systems.
• Develop and implement methods to better understand the semantics of data.
• Enable and optimize distributed training through the advancement of training libraries and components.
• Collaborate with cross-functional teams to design and build large-scale ML systems that prioritize usability, efficiency, and sustainability.
• Contribute to the development of hardware-software co-design strategies to improve training performance.
• Explore new methodologies to push the boundaries of AI systems and their applications.
• Participate in the open science community to share findings and innovations with others.

Requirements

• Master’s or Ph.D. in Computer Science, Electrical Engineering, or a related field.
• Proven experience in machine learning, particularly in systems engineering.
• Strong programming skills in languages such as Python, C++, or similar.
• Familiarity with ML libraries and frameworks such as TensorFlow, PyTorch, cuBLAS, and cuDNN.
• Experience with distributed systems and parallel computing.
• Excellent problem-solving skills and a passion for advancing AI technologies.
• Ability to work collaboratively in a fast-paced research environment.

Benefits

• Competitive salary and equity packages.
• Comprehensive health and wellness benefits.
• Flexible work hours with remote work options available.
• Opportunity to work on groundbreaking AI research projects.
• Access to continued education and professional development resources.
• A collaborative and inclusive work environment with a strong team culture.