Deep Learning Intern

📝 Deep Learning Intern (Unpaid)
⚠️ Applications will only be accepted through the following site:
👉 www.owlera.site
About Owlera
Owlera is an AI-powered career platform that helps students and fresh graduates gain practical experience through internship simulations inspired by real companies.
Participants work on realistic business challenges, receive AI-powered feedback, use modern professional tools, and build portfolio-ready projects that demonstrate their abilities to future employers.
We're looking for curious, mathematically minded, and ambitious students to join our Deep Learning Internship and gain hands-on experience training and evaluating neural networks — from feedforward architectures to CNNs, RNNs, and transformers.
About the Internship
As a Deep Learning Intern, you'll work on realistic deep learning challenges involving data preparation, model training, transfer learning, and evaluation — building neural-network models that solve realistic classification, prediction, and generation tasks.
You'll learn how deep learning practitioners take raw data and turn it into trained models — designing architectures, tuning hyperparameters, tracking experiments, and deploying simple inference pipelines.
Responsibilities
* Prepare and preprocess datasets for deep learning tasks (cleaning, normalization, augmentation).
* Build and train feedforward, convolutional (CNN), and recurrent (RNN/LSTM) networks.
* Experiment with transformer-based architectures for text and sequence tasks.
* Apply transfer learning with pre-trained models and fine-tune them on new tasks.
* Design and tune training pipelines — loss functions, optimizers, learning-rate schedules.
* Track experiments, compare model variants, and log results systematically.
* Evaluate models with proper train/validation/test splits and relevant metrics.
* Diagnose training issues such as overfitting, underfitting, and unstable gradients.
* Build simple model-serving prototypes and inference scripts.
* Visualize training curves, embeddings, and attention patterns.
* Work with GPU/accelerated training environments and batch pipelines.
* Process image, text, and tabular data for neural-network inputs.
* Write clean, readable code for experiments using PyTorch or TensorFlow.
* Document architectures, experiments, and findings clearly.
* Use modern ML tooling (notebooks, experiment trackers, cloud GPUs).
* Learn the fundamentals of backpropagation, regularization, and optimization.
* Collaborate with other interns on cross-functional AI projects.
* Turn real-world problems into trainable deep learning formulations.
Requirements
* Current student or recent graduate in Computer Science, AI, Data Science, Machine Learning, Mathematics, or a related field — or a strong self-taught coding portfolio.
* Strong interest in neural networks and deep learning.
* Basic programming skills (Python is a plus; familiarity with NumPy is a bonus).
* Comfortable with basic math — linear algebra, probability, and calculus at an introductory level.
* Analytical and logical thinking with close attention to detail.
* Self-motivated and able to work independently on technical challenges.
* Comfortable experimenting, failing fast, and iterating.
* Familiarity with AI tools such as ChatGPT, Claude, Gemini, or similar platforms is a plus.
* Previous professional deep learning experience is not required.
What You'll Gain
* Hands-on experience training real neural networks, not just theory.
* Practical experience with CNNs, RNNs, and transformer architectures.
* Experience applying transfer learning and fine-tuning pre-trained models.
* Understanding of how models are trained, evaluated, and improved.
* Practical exposure to PyTorch/TensorFlow, GPUs, and experiment tracking.
* Portfolio-ready deep learning projects built on realistic use cases.
* Personalized AI feedback on your work.
* Professional certificate upon successful completion.
* Mentorship and weekly learning sessions.
* Opportunity to strengthen your portfolio, resume, and interview readiness.
Internship Details
Role: Deep Learning Intern
Location: Remote
Type: Internship (Unpaid)
Level: Entry Level
Duration: 6 Weeks
Commitment: Flexible (approximately 10–15 hours per week)
If you're fascinated by neural networks and want to learn how real deep learning models are built, we'd love to hear from you.
⚠️ Apply through:
👉 www.owlera.site

Work arrangement
Yes