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Computer Vision Engineer InternAllus AI • San Jose, Arizona, United States
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Computer Vision Engineer Intern

Allus AI
  • US
    San Jose, Arizona, United States
  • US
    San Jose, Arizona, United States
Jetzt Bewerben

Über

Software Engineer Internship | Allus AI (YC F25) This is an internship at Allus AI. Allus AI is dedicated to building the next generation of vision intelligence systems. This role is critical for contributing to the core technology that drives these advanced systems, providing an opportunity to apply academic knowledge in a real-world, production-focused environment. As an intern, you will play a hands‑on role in developing and advancing the company’s foundational AI capabilities. TL;DR Role: Internship Mission: To contribute to the development and refinement of next-generation vision intelligence systems. Tech Stack: Python, PyTorch, CLIP, DINOv2, SAM, Florence, Qwen‑VL What You’ll Actually Do Develop and implement machine learning projects specifically focused on computer vision applications. Engage in research to advance the capabilities and understanding of vision intelligence systems. Fine‑tune and adapt advanced foundation models for various specific vision tasks and challenges. Manage the lifecycle of vision datasets, including their generation, curation, and preparation for model training. Evaluate and benchmark the performance of developed vision models to ensure accuracy and robustness. Must‑Haves Background: Student pursuing a BS, MS, or PhD in Computer Science, Machine Learning, Electrical Engineering, Robotics, or a closely related field. Experience: Demonstrated experience building machine learning projects, research projects, or open‑source contributions involving computer vision; familiarity with PyTorch or similar deep learning frameworks. Skills: Strong programming proficiency in Python; understanding of modern computer vision architectures and training workflows; strong problem‑solving ability and a willingness to learn quickly. Bonus: Practical experience training or fine‑tuning vision models; familiarity with foundation models such as CLIP, DINOv2, or SAM; contributions to ML publications, research, or open‑source projects.
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  • San Jose, Arizona, United States

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  • English
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