Role overview
We are seeking a Machine Learning Engineering Intern (preferably graduate level) to join our forward-thinking team building the next generation of Intelligent Transportation Systems. In this role, you will work alongside experienced engineers and researchers to design, develop, and evaluate computer vision models used in real-world, scalable applications.
You’ll gain hands-on experience with large-scale image and video data, contribute clean and modular code to shared repositories, and help advance production-focused machine learning systems. As part of our AI team, you’ll collaborate closely across disciplines while learning best practices in applied computer vision and MLOps.
Responsibilities
- Train, and evaluate computer vision and deep learning models for tasks such as image classification, object detection, tracking, and OCR, under guidance from senior team members.
- Prepare and analyze image and video datasets, including data augmentation, labeling strategies, and feature extraction.
- Contribute to machine learning repositories by improving and extending CNN- and transformer-based pipelines, following clean coding standards.
- Assist with data annotation and quality assurancefor image and video datasets, supporting model training and evaluation.
- Collaborate with engineering teams to integrate computer vision components into production systems.
- Stay current with academic and industry research, exploring and prototyping new approaches when relevant.
- Currently pursuing a*Master’s or PhD* in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
- Strong foundation in*machine learning and computer vision*, with exposure to deep learning methods.
- Familiarity with image processing tools such as*OpenCV* and
- Experience with*computer vision architectures*such as CNNs and ViT models.
- Proficiency in Python Language and experience with deep learning frameworks such as PyTorch or Tensorflow.
- Working knowledge of software engineering best practices, including clean code and version control (e.g., Git).
- Strong analytical skills, curiosity, and enthusiasm for applied research and real-world machine learning systems.
Benefits
- Paid days off (i.e. vacation, sick days, bereavement leave)
- Health and Dental plans
- Retirement plans
- Employee and Family Assistance Program (EFAP)
- Employee referral program
Tags & focus areas
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