Machine Learning Engineer

We are seeking an enthusiastic Machine Learning (Computer Vision) Intern to join our team on a project that's at the forefront of operational safety technology. You will focus on developing and refining segmentation and image reconstruction models that will be integral to our innovative solution. As part of our team, you will push the boundaries of what's possible with real-time image analysis and segmentation on edge devices.

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Key Responsibilities:

  • Develop visual anomalies detection algorithms using image reconstruction, object detection, and segmentation models tailored to high-resolution aerial imagery.
  • Train, test, and optimize models using large datasets, ensuring accuracy and efficiency.
  • Implement real-time processing techniques and experiment with edge deployment scenarios.
  • Collaborate with data annotators to refine datasets and improve model precision.
  • Write clean, maintainable code and assist in integrating machine learning models with the main software stack.
  • Continuously assess the latest machine learning research to enhance model performance.

Required Skills and Qualifications:

  • Strong programming skills in Python and a solid grasp of computer vision concepts.
  • Experience working with image reconstruction models and auto-encoders for visual anomalies detection.
  • Hands-on experience with convolutional neural networks (CNNs) such as U-Net, Mask R-CNN, YOLO, and GANs.
  • Familiarity with deep learning frameworks (e.g., PyTorch (preferred), TensorFlow, Keras)and image processing libraries (e.g., OpenCV, Pillow, Scikit-Image, NumPy).
  • Practical knowledge of dataset preprocessing, augmentation techniques, and model validation methods.
  • Analytical skills to interpret data and model output to drive improvements.
  • Eagerness to learn and apply the latest research in machine learning, computer vision, and anomalies detection.
  • Experience in deploying AI models on edge devices is a plus.

Benefits:

  • Direct involvement in a project with real-world impact and the potential for widespread adoption.
  • Access to cutting-edge technology and high-performance computing resources.
  • Collaborative environment with mentorship from leading experts in the machine learning and computer ¬†vision field.
  • Potential for your work to contribute to industry-leading research and development.
  • Academic credit, if applicable, and a pathway to full-time employment post-internship.

Additional Notes:

  • Applicants must be prepared to sign a non-disclosure agreement (NDA) before the full details of the project can be disclosed.
  • Prior coursework or projects in computer vision or related fields will be viewed favorably.
  • Initiative and the ability to work autonomously, as well as part of a team, are essential.

Join us and contribute to groundbreaking advancements in operational safety technology through the power of machine learning and computer vision 

Apply Here