Computer Vision / Applied AI Intern at Simbe

About The Role

Join Simbe, a company focused on transforming retail intelligence through computer vision technology. As a Computer Vision / Applied AI Intern, you will gain hands-on experience applying computer vision and machine learning to real-world data and production systems. You will work on a scoped project aligned with the team's priorities, develop and evaluate solutions using Python and modern ML frameworks, and collaborate with engineers across various technical teams. This internship offers a unique opportunity to contribute to meaningful work alongside a full-time engineering team.

Contribuer à un projet défini aligné sur les priorités de l'équipe de vision par ordinateur / IA appliquée, en développant, testant et évaluant des solutions.
Travailler avec des ensembles de données d'images de production pour identifier des modèles, des modes de défaillance et des opportunités d'amélioration.
Collaborer avec des ingénieurs d'autres équipes techniques et communiquer les progrès, les décisions techniques et les résultats.

Familiarity with Git or another source-control system
Experience with pandas, NumPy, OpenCV, Jupyter, SQL, or related data and ML tooling
Previous internship, research, or project experience involving computer vision or machine learning
We primarily target students in their final year of study and will also consider strong juniors
Experience with PyTorch, TensorFlow, or a comparable machine learning framework
Experience with AI-assisted coding and engineering tools and the ability to thoughtfully validate generated output
Coursework or hands-on experience in computer vision, machine learning, or deep learning
Experience with object detection, image segmentation, OCR, barcode recognition, image classification, or related vision problems
Experience working with structured Python projects beyond notebooks alone
Comfortable working with data to evaluate results, investigate failures, and support technical decisions
Currently pursuing a BS, MS, or PhD in Computer Science, Computer Engineering, Robotics, Machine Learning, Data Science, or a related technical field
Experience creating, cleaning, curating, or evaluating image datasets
Strong communication and collaboration skills
Familiarity with Linux, shell scripting, Docker, or cloud-based development environments
Strong Python programming skills, including familiarity with common data structures, algorithms, and software development practices
Familiarity with model evaluation techniques, error analysis, experiment tracking, or data-quality workflows
Personal computer vision, machine learning, robotics, or software projects outside of coursework
Strong technical problem-solving skills and willingness to work through ambiguous or unfamiliar problems