Rigetti is seeking a motivated student (Bachelor’s, Master’s, or PhD in CS, SWE, or related field) to develop a production-oriented, on-premise data automation and computer vision solution. This is an applied engineering role focused on building operational systems intended for future production integration rather than academic research.
The intern will develop a Python backend to process structured inspection data and apply image classification, design a retrainable model workflow, and contribute to a lightweight web UI for reviewing results. The intern will work closely with Defect Metrology and Software Engineering teams to ensure domain accuracy and production-quality implementation. This role is ideal for students pursuing industry careers in software engineering, machine learning engineering, or applied AI.
Educational Value
Gain hands-on experience building a production-oriented computer vision system in an industrial environment. The internship provides exposure to backend automation, machine learning integration, retraining workflows, and lightweight full-stack development. Skills developed align directly with industry roles in Software Engineering, Machine Learning Engineering, and Applied AI.
Key Responsibilities
Backend / Data Processing
Develop Python automation for structured file processing (CSV/Excel)
Implement robust filesystem logic and idempotent processing
Design outputs suitable for production integration
Add logging, configuration management, and documentation
Computer Vision
Implement, integrate, and validate an on-prem image classification model
Design a retraining workflow to incorporate new labeled data
Support model evaluation, performance analysis, and versioning
Front-End UI
Contribute to a lightweight web UI (TypeScript, HTML, CSS)
Display and filter structured inspection results and images
Support workflow for review and retraining selection
Required Qualifications
Pursuing a Bachelor’s, Master’s, or PhD in CS, SWE, or related field
Strong Python skills
Experience working with structured data and filesystems
Solid software engineering fundamentals
Ability to independently manage a scoped 12-week engineering project
Preferred Qualifications
Coursework or experience in computer vision or image classification
Familiarity with ML frameworks (PyTorch, TensorFlow, etc.)
Experience with TypeScript, HTML, CSS
Interest in applied, production-oriented machine learning systems
As engineering leaders, we value diversity and are committed to building a culture of inclusion to attract and engage innovative thinkers. Our technology, meant to serve all of humanity, cannot succeed if those who built it do not mirror the diversity of the communities we serve. Applications from women, minorities, and other under-represented groups are encouraged.
About Rigetti
Rigetti Computing is a pioneer in full-stack quantum computing. The company has operated quantum computers over the cloud since 2017 and serves global enterprise, government, and research clients through its Rigetti Quantum Cloud Services platform. The company’s proprietary quantum-classical infrastructure provides ultra-low latency integration with public and private clouds for high-performance practical quantum computing. Rigetti has developed the industry’s first multi-chip quantum processor for scalable quantum computing systems. The company designs and manufactures its chips in-house at Fab-1, the industry’s first dedicated and integrated quantum device manufacturing facility. Rigetti was founded in 2013 and today employs more than 150 people with offices in the United States, U.K., and Australia. Learn more at www.rigetti.com.
Don't see the job you want? Apply here so we can keep in touch with you when the right role opens up in the future!
Export Licensing Compliance
Rigetti is committed to full compliance with applicable anti-discrimination laws. We are an equal opportunity employer and value diversity at our company. We strive to create an inclusive work environment and will not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
