Student Machine Learning Engineer
Auburn University Auburn, Alabama, United States · $31K–$36K/yr
Primary and Secondary Education · 2-10 employees
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About the role
The Student Machine Learning Engineer will train, test, and evaluate AI models using PyTorch. They are also responsible for handling large datasets and coding projects to specific requirements.
What they look for
Requirements
Candidates must be currently enrolled students at Auburn University pursuing a degree in Computer Science or a related field. Applicants should have experience with machine learning modeling, deep learning architectures, and Python.
Full description
Overview
The RFID Lab at Auburn University is looking for a Student Machine Learning Engineer. This role is dedicated to creating, expanding, and refining the abilities of machine learning models ran at the RFID Lab.
Responsibilities
The Student Machine Learning Engineer will:
- Train, test, and evaluate ML/AI models using PyTorch
- Handle large datasets using Python
- Code ML/AI projects to specification
Qualifications
- Enrolled student at Auburn University
- Computer Science or related degree
- Experience with ML modeling
Minimum Knowledge, Skills, and Abilities
- Python
- Pytorch
- Experience in deep learning architectures such as CNNs, transformers, etc.
- Experience handling large datasets using Python
- Fundamental knowledge in RF
Why Work at Auburn?
Why should YOU consider student employment at Auburn University?
- Gain valuable work experience! Student employment allows you to explore different interests, identify strengths, and make informed decisions about your future career goals.
- Build your network! Interacting with faculty, staff, and fellow students can lead to valuable connections and potential mentors.
- Make a difference! Have the satisfaction of knowing YOU are a part of providing the premier academic experience at Auburn and the life-changing work our students and employees perform.
Equal Opportunity Compliance Statement
It is our policy to provide equal employment and education opportunities for all individuals without regard to race, color, national origin, religion, sex, sexual orientation, gender identity, gender expression, pregnancy, age, disability, protected veteran status, genetic information, or any other classification protected by applicable law. Please visit the Office of Equal Opportunity Compliance's website to learn more.
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