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