AI Project Intern – Computer Vision
Newegg
Job Overview
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Job Description
Purpose of Job
We are seeking a motivated AI Project Intern – Computer Vision to support our warehouse and logistics automation initiatives, with a focus on document analysis and video analysis. This internship provides hands-on experience in applying cutting-edge AI technologies to solve real-world supply chain challenges. The ideal candidate is passionate about computer vision, eager to learn, and excited to collaborate with cross-functional teams in a fast-paced e-commerce environment.
Job Description
Apply computer vision techniques to automate warehouse and logistics workflows, such as:
- Develop and deploy computer vision models for object detection, tracking, and anomaly detection in logistics workflows (e.g., pallet counting, dock monitoring, trailer in/out verification).
- Build and maintain OCR and document understanding pipelines for extracting structured data from BOLs, ASNs, invoices, packing lists, and other logistics PDFs.
- Integrate camera-based recognition systems (e.g., license plate recognition, packed item verification, activity recognition) into warehouse operations.
- Collaborate with operations teams to validate AI outputs against real logistics scenarios.
- Assist in developing prototypes, testing models, and refining algorithms to improve accuracy and efficiency.
- Support documentation of processes, findings, and best practices for ongoing projects.
Job Requirements
- Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field.
- Strong academic or project experience in computer vision, deep learning, or machine learning.
- Familiarity with libraries and frameworks such as OpenCV, TensorFlow, or PyTorch.
- OCR & Document AI: Tesseract, PaddleOCR, LayoutLM, Donut, or commercial services (AWS Textract, Google Vision, Azure Form Recognizer).
- Solid programming skills in Python (preferred) or similar languages.
- Strong analytical and problem-solving abilities.
- Excellent communication and collaboration skills, with the ability to work closely with both technical and operations teams.
Preferred Skills
- Prior project or internship experience applying AI/ML in logistics, supply chain, or manufacturing environments.
- Knowledge of warehouse management systems or logistics processes.
Essential Mental & Physical Function
Decisions may affect a work unit or area within a department. May contribute to business and operational decisions that affect the department. This position performs a variety of routine duties within established policies and procedures or by referral to supervisor's guidelines.
Supervisor Responsibilities
N/A
Language Skills
Must be able to read and understand English.
Work Environment
Standard office working environment.
Travel Requirements
N/A
Key skills/competency
- Computer Vision
- Deep Learning
- Machine Learning
- Python
- TensorFlow
- PyTorch
- OCR
- Object Detection
- Anomaly Detection
- Logistics Automation
How to Get Hired at Newegg
- Research Newegg's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor, focusing on their innovation in e-commerce and supply chain.
- Tailor your resume: Customize your application to highlight academic projects or practical experience in computer vision, deep learning, machine learning, and logistics automation, directly addressing the requirements for the AI Project Intern – Computer Vision role.
- Showcase technical skills: Emphasize proficiency in Python, and familiarity with key libraries like OpenCV, TensorFlow, PyTorch, and OCR/Document AI tools such as Tesseract or AWS Textract.
- Prepare for technical interviews: Be ready to discuss your experience with computer vision algorithms, model development, and problem-solving scenarios relevant to warehouse automation and document analysis.
- Demonstrate collaboration and problem-solving: Practice articulating how you’ve worked effectively in teams and approached complex technical challenges, aligning with Newegg's fast-paced environment.
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