Platform Engineering Machine Learning Intern

Impinj•Seattle, WA

5h•$26 - $40•Hybrid

About The Position

Impinj is a leading RAIN RFID provider and Internet of Things pioneer. We’re inventing ways to connect every thing to the Internet — including retail apparel, retail general merchandise, healthcare items, automobile parts, airline baggage, food and much more. With more than 100 billion items connected to date, and multiple Fortune 500 enterprises around the world using our platform, we solve for a better understanding of our world. If it’s a thing, we’re working to connect it. Join Impinj and help us realize our vision of a boundless IoT— connecting trillions of everyday items to the Internet. Team Overview: Impinj is seeking a Platform Team Machine Learning Intern specializing in Machine Learning to join our Platform Engineering team. This role will work closely with one of our Technical Fellows. As an intern, you will have the opportunity to work with engineers, technologists, and external partners to help enrich your career focus in tiny machine learning applications. What You Will Do: Develop and implement comprehensive test cases to verify the functionality and performance of tiny machine learning models used to create consumable events from raw RAIN RFID detection data, including understanding the model's expected behavior and designing test scenarios that cover edge cases and potential failure points Analyze test results, identify issues, debug code, and propose fixes to ensure models perform reliably under various conditions Work closely with the development team to understand model requirements and goals, ensuring tests align with project objectives and that issues are promptly communicated and resolved Maintain detailed and organized documentation of all test cases, results, and issues to track progress and support future testing and knowledge sharing across the team Recommend and implement improvements to the testing process by applying updated testing methodologies, tools, and best practices to improve model quality and reliability Contribute to ongoing model development efforts Why Intern with Impinj: The Impinj Summer Internship Program is designed to provide undergraduate and graduate students with a comprehensive learning experience that goes beyond traditional work assignments. It offers a unique blend of professional development, mentorship, and networking opportunities to help interns thrive in their roles and prepare for successful careers. Students develop valuable skills through interactive learning sessions and receive personalized mentorship and guidance from early-career colleagues. The program offers more than just a resume boost. It’s a chance to access hands-on experience, leadership insights, and a network of peers and mentors that lasts well beyond the summer. Learn what our interns last year had to say about their experience: Impinj Intern Program: A Season of Learning, Connection, and Fun (Impinj blog) . This Summer Internship Cohort begins on Monday, June 15 and ends September 4. The start date is firm; the end date is flexible to end early. All internship positions report at least on a hybrid basis to our Seattle office. There is opportunity for full time employment for those graduates or those entering their senior year. Compensation & Benefits: The benefits listed below may vary depending on the nature of your employment with Impinj and the country where you work. The typical base pay range for this role across the US is $26.00/hr - $40.00/hr . Individual base pay depends on various factors such as complexity and responsibility of role, job duties, requirements, and relevant experience and skills. Both market wage data and the mid-point of the pay range is reviewed and used as the starting point for all new hire offers. Offers are made within the base pay range applicable at the time. At Impinj certain roles are eligible for additional rewards, including merit increases, annual bonus and stock. These awards are allocated based on individual performance. In addition, certain roles also have the opportunity to earn sales incentives based on revenue or utilization, depending on the terms of the plan and the employee’s role. US based employees have access to healthcare benefits; a 401(k) plan and company match among others. For a more comprehensive list of US employment benefits, click here . US Export Controls: This position has access to technologies or data subject to U.S. export control regulations. Under these laws, the release or transfer of export-controlled items or information to individuals who are not classified as

Requirements

Currently enrolled in a Bachelor's, Master's, or PhD program in Computer Science, Data Science, Software Engineering , or a related technical field
Proficiency in Python (specifically libraries like Pandas, NumPy, and Scikit-learn)
Strong command of Git and GitHub/GitLab workflows
Exposure to at least one major ML framework (PyTorch or TensorFlow)
A natural drive to explore and experiment
New ideas and approaches to problem-solving.
A strong eagerness to learn and contribute to the team
Demonstrated ability to notice and identify subtle details and issues
Clear communication skills and ability to document technical information for a variety of intended audiences

Responsibilities

Develop and implement comprehensive test cases to verify the functionality and performance of tiny machine learning models used to create consumable events from raw RAIN RFID detection data, including understanding the model's expected behavior and designing test scenarios that cover edge cases and potential failure points
Analyze test results, identify issues, debug code, and propose fixes to ensure models perform reliably under various conditions
Work closely with the development team to understand model requirements and goals, ensuring tests align with project objectives and that issues are promptly communicated and resolved
Maintain detailed and organized documentation of all test cases, results, and issues to track progress and support future testing and knowledge sharing across the team
Recommend and implement improvements to the testing process by applying updated testing methodologies, tools, and best practices to improve model quality and reliability
Contribute to ongoing model development efforts