Intern, Software Engineering -… at PsiQuantum · Palo Alto

Summary: PsiQuantum is focused on building the first useful quantum computers to deliver groundbreaking solutions across various industries. The intern will support the team in developing a scalable scientific computing workflow, enhancing reliability and usability through automation and validation. Responsibilities: - Contribute to hardening a chemistry-to-quantum resource estimation pipeline: robustness, scalability, reproducibility, and “push-button” usability - Implement and validate stable interfaces/data contracts between core modules (inputs/outputs/metadata/schema checks) - Help automate execution of a predefined benchmark suite across both cloud GPU environments and internal HPC clusters (job submission, retries, artifact collection, deterministic configs) - Support expansion of an end-to-end scientific computation workflow by implementing integration layers, validation, and test coverage for new upstream inputs, additional computational backends, and alternative algorithmic paths within a single, consistent execution framework - Implement a representative application workflow that exercises the pipeline across a structured set of related inputs (parameter sweeps), automates repeated executions, aggregates outputs into analysis-ready artifacts, and documents key assumptions, approximations, and major sources of error/uncertainty - Implement secure, automated sharing of HPC outputs to cloud object storage (e.g., S3) for downstream analysis and collaboration Required Qualifications: - Enrolled in a BS/MS/PhD in CS, EE, Physics, Chemistry, Applied Math, or related field - Strong Python software engineering: clean APIs, testing, packaging, logging, configuration management - Familiarity with quantum computing applications/algorithms (resource estimation, simulation, or related) sufficient to validate computational outputs - Solid scientific computing foundations (linear algebra, numerical methods, data handling) - Experience with quantum chemistry workflows (molecular geometries, integrals formats, active space concepts, common solver outputs) Preferred Qualifications: - Experience with HPC environments (batch schedulers, containers/modules, scaling, reproducible runs) - Experience designing benchmark harnesses and performance profiling - Experience with cloud object storage and data pipelines (S3-style storage, provenance/metadata, artifact versioning) Required Skills: Python, Quantum computing, Scientific computing Important Skills: HPC environments, Cloud object storage Nice-to-Have Skills: Data handling, Numerical methods, Testing, Configuration management Benefits: Housing/Commuter Stipend