Computational Chemist - GPU Acceleration

Job Description

Job Title: Computational Chemist - GPU Acceleration. Location: Palo Alto, California, United States

Responsibilities:

• Develop, implement, and optimize computational chemistry and electronic-structure algorithms for GPU-accelerated platforms.
• Design scientific software that efficiently uses NVIDIA and AMD GPUs as well as conventional CPU-based HPC systems.
• Profile and optimize computational kernels, memory movement, parallelism, and complete scientific workflows.
• Improve the performance and scalability of computational chemistry applications;
• Develop computational pipelines combining classical HPC and GPU approaches with fault-tolerant quantum-computing workflows.
• Identify computational bottlenecks in electronic-structure and quantum-chemistry methods and develop software and algorithmic solutions.
• Implement and optimize numerical methods including tensor contractions, linear algebra, iterative solvers, and related computational primitives.
• Work with computational chemists and quantum algorithm researchers to benchmark and validate GPU-accelerated classical methods against emerging quantum algorithms.
• Contribute to scalable scientific software for molecular and materials simulations;
• Evaluate emerging GPU programming frameworks, libraries, and hardware capabilities for computational chemistry applications.
• Participate in scientific collaborations across chemistry, physics, materials science, quantum computing, and high-performance computing.
• Document software and research results.
• Contribute to internal technical reports, scientific publications, and presentations.

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, such as CUDA, HIP/ROCm, or comparable frameworks.
• Experience with NVIDIA and/or AMD GPU architectures;
• Understanding of GPU performance considerations including 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.
• Ability to work effectively within large scientific software codebases.
• Experience profiling, benchmarking, and optimizing scientific applications.
• Strong numerical and computational problem-solving skills.
• Ability to translate mathematical algorithms into efficient software implementations.
• Ability to work collaboratively in an interdisciplinary research environment covering chemistry, physics, materials science, HPC, and quantum computing.

Preferred:

• Experience developing GPU implementations of electronic-structure or quantum-chemistry methods.
• Experience with both NVIDIA CUDA and AMD HIP/ROCm, including porting or maintaining scientific software across GPU architectures.
• Experience optimizing complete computational pipelines, including CPU/GPU scheduling, asynchronous execution, data movement, and distributed GPU workloads.
• Experience with GPU-accelerated scientific libraries or frameworks for dense or sparse linear algebra, tensor operations, FFTs, or related numerical workloads.
• Experience with distributed-memory HPC environments using MPI and multi-GPU computing;
• Experience developing 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 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 for multiple accelerator architectures.
• Strong record of scientific software contributions and/or peer-reviewed publications.

Benefits and Compensation:

PsiQuantum offers a comprehensive total compensation package.

Base salary ranges:

• Zone 1, Bay Area and NYC: $151,800 to $178,400 per year
• Zone 2, including Los Angeles and Washington, DC: $136,700 to $160,600 per year
• Zone 3, including Austin, Chicago, and Sacramento: $121,500 to $142,700 per year
• Zone 4, including Nashville, Phoenix/Tempe, and many remote locations: $106,300 to $124,900 per year

Actual compensation depends on qualifications, education, training, experience, location, business needs, and internal equity.

Full-time employees are eligible for:

• Competitive health coverage for employees and dependents
• 401(k) with company match
• Equity grants
• Financial wellness tools and planning resources
• Wellness benefits
• Family support programs
• Life and disability insurance
• Paid leave programs
• Company-designated paid holidays
• Discretionary time off
• End-of-year company shutdown

Some benefits have eligibility requirements and may vary by location, role, or employment status. Many benefits are subsidized or fully paid by PsiQuantum.