AI/ML Engineer Intern

Summary

• Join ShelfEx's AI team to build next-generation intelligent systems that blend Computer Vision, Generative AI, and Retail Analytics.
• You will develop scalable models and pipelines that run on edge and cloud, turning shelf images and product data into real-time business insights.

Roles & Responsibilities

• Design and train deep learning models for computer vision tasks such as object detection, segmentation, and pose estimation on shelf/product images.
• Develop generative AI models (vision-to-text, summarization, LLM prompting) to enhance insight generation for retail analytics.
• Build robust data pipelines to handle millions of images, metadata, and sales data — enabling continuous training and evaluation.
• Optimize and deploy models for edge inference with constraints on latency and compute.
• Collaborate with analytics and product teams to align ML outputs with customer impact.
• Conduct A/B testing and model benchmarking for real-world performance evaluation.
• Publish internal research notes and present progress in weekly technical reviews.

Qualifications

• Strong understanding of machine learning fundamentals, computer vision, and deep learning architectures (CNNs, transformers, etc.).
• Proficiency in Python and hands-on experience with PyTorch or TensorFlow.
• Experience working with CV datasets, image augmentations, and ML pipelines.
• Basic exposure to Generative AI concepts like text generation, embeddings, or vision-language models.
• Ability to write clean, modular, and testable ML code and use version control (Git).

Tech Stack

Required: Python, PyTorch, TensorFlow, OpenCV

Optional: Hugging Face Transformers, AWS SageMaker, ONNX, FastAPI, Docker, LangChain, Weights & Biases, scikit-learn, Pandas