Role description
Deep Learning Engineer (Fresher)
Remote (worldwide)Full-time0-2 years experience₹4 to ₹8 LPA
We are hiring a deep learning engineer to build and train neural networks end to end. You will work on computer vision and sequence models with PyTorch and TensorFlow, tune them until they perform, and document what actually worked so learners can follow the same path.
What you will do
- Design and train CNNs, RNNs, and transformer models
- Build image classification and object detection pipelines
- Run experiments, tune hyperparameters, and track results
- Keep training efficient with GPUs and well-built data pipelines
- Convert strong experiments into tutorial case studies
What we look for
- 0 to 2 years of deep learning experience (course projects count)
- Hands-on PyTorch or TensorFlow experience beyond tutorials
- Understanding of backpropagation, loss functions, and regularization
- Solid Python and NumPy
- Ability to read a paper and implement its core idea
Nice to have
- Published models, Kaggle medals, or open-source work
- Experience with detection or diffusion models
- Experience training on cloud GPUs or Colab
Skills
PyTorchTensorFlowCNNsComputer visionNumPyPython
Applications are closed
We have paused hiring, so we are not accepting applications for this role at the moment and resumes sent by email will not be reviewed. This page stays up so you can see what the role involves and what we look for. The application form returns here when hiring reopens.
In the meantime, our free AI and ML tutorials cover most of the skills listed here.