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Building the world’s first useful quantum computer.
Intern, Software Engineering
Location
California
Posted
123 days ago
Salary
$27 - $47 / hour
Seniority
Entry Level
Job Description
Intern, Software Engineering
PsiQuantum
• Implement governance patterns for datasets and run outputs (naming, lineage, access boundaries, catalog/volume organization). • Improve dataset upload validation and guardrails to prevent accidental modification of unrelated storage paths and to enforce consistent metadata and file structure • Build monitoring and reporting for compute usage and cost drivers (job frequency, runtime, GPU utilization proxies, storage growth, auto-termination effectiveness). • Deliver dashboards that make platform health and spend understandable to both engineers and researchers. • Refactor existing job setup / submission scripts into a maintainable, testable OOP design (clear interfaces, configuration objects, reusable clients). • Improve workflow parameter handling for the two-stage pipeline (tensor factorization stage and QRE stage) and standardize outputs for downstream analysis. • Reduce onboarding friction by abstracting authentication and setup into a single, ergonomic path (e.g., a CLI/Python entry point that validates auth, environment, and required dependencies). • Replace “follow the guide manually” with automation: preflight checks, actionable errors, and self-serve setup validation.
Job Requirements
- Currently pursuing BS/MS/PhD in Computer Science, Engineering, Physics, Math, or related field.
- Strong Python skills, including clean API design, OOP, packaging, and testing.
- Working knowledge of distributed/remote compute concepts (jobs, clusters, queues) and cloud storage fundamentals.
- Familiarity with quantum computing applications/algorithms (resource estimation, quantum simulation, or adjacent numerical methods); comfort with linear algebra and scientific computing.
- Databricks experience (Jobs API/SDK, workspace organization, catalog/permissions patterns).
- AWS experience (S3, IAM/credentials handling, boto3-style tooling, cost monitoring patterns).
- Experience with scientific Python stacks and GPU compute (JAX/NumPy/SciPy; performance profiling).
- Exposure to quantum chemistry workflows, tensor factorization, or benchmark-driven research engineering.
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