Computational Chemist - GPU Acceleration

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

Computational Chemist - GPU Acceleration at PsiQuantum, Palo Alto, California, United States (remote). A mid-level full time position in the Engineering team, listed under business operations.

PsiQuantum's mission is to build the first useful quantum computers: machines capable of delivering the breakthroughs the field has long promised. Since our founding in 2016, our singular focus has been to build and deploy million-qubit, fault-tolerant quantum systems. Quantum computers harness the laws of quantum mechanics to solve problems that even the most advanced supercomputers or AI systems will never reach. Their impact will span energy, pharmaceuticals, finance, agriculture, transportation, materials, and other foundational industries. Our architecture and approach is based on silicon photonics. By leveraging the advanced semiconductor manufacturing industry, including partners like GlobalFoundries, we use the same high-volume processes that already produce billions of chips for telecom and consumer electronics. Photonics offers natural advantages for scale: photons don't feel heat, are immune to electromagnetic interference, and integrate with existing cryogenic cooling and standard fiber-optic infrastructure. That approach has since been tested at the highest level of scrutiny the U.S. government applies to emerging technology, and it has held up. In 2025, PsiQuantum closed a $1 billion funding round that valued the company at $7 billion. In 2026, the U.S. Department of Commerce signed a $100 million Letter of Intent under the CHIPS and Science Act, followed by a $125 million agreement with DARPA under Stage C of its Quantum Benchmarking Initiative, PsiQuantum's most valuable U.S. government agreement to date. This year, we also broke ground on our utility-scale quantum computer in Brisbane, Australia, and continued building out our Chicago site. Victor Peng, our CEO, and co‑founder Jeremy O'Brien, now Executive Chairman, lead a team and board that reflects how seriously the world is taking this build, joined this year by Intel's Lip‑Bu Tan and Atomico's Niklas Zennström. PsiQuantum also develops the algorithms and software needed to make these systems co

Requirements

• Ph.D.in computational chemistry, theoretical chemistry, computational physics, materials science, computer science, or a closely related field, or equivalent relevant 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, for example using CUDA, HIP/ROCm, or comparable GPU programming frameworks.
• Experience working with NVIDIA and/or AMD GPU architectures and understanding of GPU performance considerations such as memory hierarchy, data movement, parallel execution, and kernel performance.
• Strong experience with high-performance computing and parallel scientific workloads.
• Proficiency in scientific programming and algorithm development using C++, C, Fortran, and/or Python, with the ability to work effectively in large scientific software codebases.
• Experience profiling, benchmarking, and optimizing scientific applications.

Nice to Have

• Experience developing GPU implementations of electronic-structure or quantum-chemistry methods.
• Experience with both NVIDIA CUDA and AMD HIP/ROCm ecosystems, including porting or maintaining scientific software across GPU architectures.
• Experience optimizing large computational pipelines rather than individual kernels alone, including CPU/GPU scheduling, asynchronous execution, data movement, and distributed GPU workloads.
• Experience with GPU-accelerated scientific libraries or frameworks for dense/sparse linear algebra, tensor operations, FFTs, or related numerical workloads.
• Experience with distributed-memory HPC environments using technologies such as MPI in combination with multi-GPU computing.
• Experience developing, extending, or contributing to large-scale scientific software for electronic structure, quantum chemistry, or materials modeling.