Math Libraries Intern, cuEST - Summer 2027
Core
Develop GPU-accelerated algorithms and numerical methods for quantum chemistry primitives in the cuEST CUDA-X math library.
Role type
Software engineering intern (math libraries)
Builds
cuEST, a production CUDA-X library for electronic structure computations
Domain
Quantum chemistry / High-performance computing
Deliverable
production ML models
Required skills
C/C++ programming, Python programming, algorithms, numerical methods, performance analysis, test design
Preferred skills
GPU programming (CUDA/OpenCL), quantum chemistry research, floating-point arithmetic, hardware architecture knowledge, agentic AI tools
Responsibilities
Prototype GPU-accelerated algorithms for quantum chemistry primitives, analyze and improve CUDA implementation performance, contribute to design and testing, collaborate with stakeholders on application needs
Seniority
Intern
