Computational Chemist - GPU Acceleration

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 commercially valuable. Our application, software, and industry teams work directly with leading Fortune 500 companies, including Airbus, Lockheed Martin, Mercedes-Benz, Boehringer Ingelheim, and Mitsubishi Chemical, to prepare quantum solutions for real-world impact. 

Quantum computing is not an extension of classical computing. It represents a fundamental shift, and a path to mastering challenges that cannot be solved any other way. The potential is enormous, and we now have the funding, the government validation, and the sites under construction to make it real. 

Job Summary:

Want to be at the forefront of using high-performance computing, GPU acceleration, computational chemistry, and quantum computing to solve challenging problems in chemistry and materials science? 

PsiQuantum is seeking a Computational Chemist with strong GPU acceleration and scientific software development expertise to join our Quantum Solutions team. You will develop and optimize computational chemistry algorithms and scientific workflows for modern heterogeneous computing platforms, with particular emphasis on AMD and NVIDIA GPUs. 

You will work at the intersection of computational chemistry, electronic-structure theory, high-performance computing, and fault-tolerant quantum computing. A major focus of this role will be accelerating computationally demanding chemistry workloads, improving end-to-end computational pipelines, and enabling efficient integration between classical HPC/GPU calculations and emerging quantum-computing workflows. 

You will collaborate closely with computational chemists, quantum algorithm researchers, and scientific software developers to identify performance bottlenecks, design scalable numerical algorithms, and translate state-of-the-art computational chemistry methods into robust, high-performance implementations. 

This role offers the opportunity to conduct publishable scientific research while developing computational capabilities that can operate at the scale required for industrially relevant chemistry and materials problems.

Responsibilities:

• Develop, implement, and optimize computational chemistry and electronic-structure algorithms for GPU-accelerated computing platforms.
• Design scientific software capable of efficiently utilizing NVIDIA and AMD GPU architectures, as well as conventional CPU-based HPC systems.
• Profile and optimize computational kernels, memory movement, parallelism, and end-to-end scientific workflows to improve performance and scalability.
• Develop computational pipelines that combine best-in-class classical approaches, including HPC and GPU acceleration, with fault-tolerant quantum-computing workflows.
• Identify computational bottlenecks in electronic-structure and quantum-chemistry methods and develop algorithmic and software solutions to address them.
• Implement and optimize numerical methods relevant to electronic-structure calculations, including tensor contractions, linear algebra, iterative solvers, and related computational primitives.
• Work closely with computational chemists and quantum algorithm researchers to benchmark and validate GPU-accelerated classical methods against emerging quantum algorithms.
• Contribute to the architecture and development of scalable scientific software used for molecular and materials simulations.
• Evaluate emerging GPU programming frameworks, libraries, and hardware capabilities and determine how they can improve computational chemistry workloads.
• Participate in scientific collaborations and technical discussions across chemistry, physics, materials science, quantum computing, and high-performance computing teams.
• Document software and research results and contribute to internal technical reports, scientific publications, and presentations. 

Experience/Qualifications:

• 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.
• Strong numerical and computational problem-solving skills and the ability to translate mathematical algorithms into efficient software implementations.
• Ability to work effectively in a collaborative, interdisciplinary research environment spanning chemistry, physics, materials science, HPC, and quantum computing. 

Preferred Qualifications 

• 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.
• Experience with DMRG, tensor-network methods, or other strongly correlated electronic-structure methods, particularly implementations involving large tensor contractions or GPU acceleration.
• Experience with coupled-cluster, configuration-interaction, multireference, or other advanced wave-function-based electronic-structure methods.
• Experience with quantum embedding, localized orbital methods, active-space approaches, or reduced electronic models derived from first-principles calculations.
• Experience applying or evaluating quantum-computing algorithms for electronic-structure, chemistry, or materials-science applications.
• Experience developing portable performance-critical software targeting multiple accelerator architectures.
• Strong track record of scientific software contributions and/or peer-reviewed publications. 

PsiQuantum provides equal employment opportunity for all applicants and employees. PsiQuantum does not unlawfully discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, military or veteran status, marital status, domestic partner status, sexual orientation, genetic information, or any other basis protected by applicable laws.

Note: PsiQuantum will only reach out to you using an official PsiQuantum email address and will never ask you for bank account information as part of the interview process. Please report any suspicious activity to [email protected].

We are not accepting unsolicited resumes from employment agencies.