Stelvio Inc. · 11 hours ago
Machine Learning Intern
Frisco, TX
Internship
Onsite
InternStelvio Inc. is seeking a Machine Learning Engineering Intern to join their 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 applications.
Staffing & Recruiting
Hiring Manager
Sophie Clegg
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 assurance for 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
Qualification
Required
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 PIL
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
Preferred
Graduate level
Company
Stelvio Inc.
Matching talented people with innovative companies across the US. We care, we are tenacious and we deliver results, consistently.
Founded in 2022
11-50 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase