Position Overview
As a Deep Learning Engineer Intern, you will work closely with our development team to design, implement, and optimize deep learning models for various applications. You will have the chance to work on challenging projects, leveraging your expertise in deep learning, machine learning, and computer vision to make significant contributions to our AI initiatives. This internship is an excellent opportunity to further develop your skills, learn from experienced professionals, and make a meaningful impact in the field of AI.
Key Responsibilities
- Collaborate with senior deep learning engineers to develop and implement deep neural networks and machine learning algorithms.
- Preprocess and analyze large datasets to extract meaningful insights and features.
- Fine-tune existing deep learning models and optimize them for performance.
- Experiment with different architectures and techniques to improve model accuracy and efficiency.
- Work on computer vision tasks, such as image classification, object detection, and segmentation.
- Document your work, including code, experiments, and research findings.
Qualifications
- Completed a Bachelor’s or Master’s degree in Computer Science.
- Strong understanding of deep learning concepts, including neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transfer learning.
- Proficiency in programming languages such as Python and familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch).
- Experience with data preprocessing, feature engineering, and data visualization.
- Solid mathematical foundation in linear algebra and calculus.
- Excellent problem-solving skills and the ability to think critically.
- Strong communication and teamwork skills.
- Prior experience with AI-related projects or internships is a plus.
What You’ll Gain
- Hands-on experience in the field of deep learning and artificial intelligence.
- Mentorship from experienced deep learning engineers and researchers.
- The opportunity to work on real-world projects with practical applications.
- The chance to contribute to the advancement of AI technology.