GPU-Accelerated Quantum Chemist (Remote)

Entangled Future; Palo Alto (CA); Hybrid; USD 150,000 - 190,000; Full time

Job summary

PsiQuantum in Palo Alto seeks a mid-level Computational Chemist to advance GPU-accelerated quantum chemistry workflows. You will contribute to high-performance software, optimize kernels, and collaborate with physics and software teams in a remote-friendly environment.

Required Ph.D. or equivalent experience, strong background in density functional theory or related methods, and proficiency with CUDA/HIP and C++, Python. Experience with multi-GPU workloads is a plus.

Qualifications

• Ph.D. in computational chemistry, theoretical chemistry, computational physics, materials science, computer science, or closely related field, or equivalent experience.
• Strong understanding of computational chemistry or electronic-structure methods, such as density functional theory, wave-function-based quantum chemistry, atomistic simulation, or related numerical methods.
• Demonstrated experience developing or optimizing GPU-accelerated scientific software.
• Experience programming for GPU or heterogeneous computing environments (CUDA, HIP/ROCm, etc.).
• Experience with NVIDIA/AMD GPUs and memory/parallel performance considerations.
• Strong HPC experience and parallel scientific workloads.
• Proficiency in C++, C, Fortran, Python in large scientific codebases.
• Experience profiling, benchmarking, and optimizing scientific applications.

Skills

GPU programming

HPC workloads

Languages: C/C++/Python/Fortran

CUDA/HIP programming

GPU architectures knowledge

Education

Ph.D. in relevant field

Tools

CUDA

HIP/ROCm

MPI

Multi-GPU scheduling

FFT libraries

Job description

PsiQuantum in Palo Alto seeks a mid-level Computational Chemist to advance GPU-accelerated quantum chemistry workflows. You will contribute to high-performance software, optimize kernels, and collaborate with physics and software teams in a remote-friendly environment.

Required Ph.D. or equivalent experience, strong background in density functional theory or related methods, and proficiency with CUDA/HIP and C++, Python. Experience with multi-GPU workloads is a plus.