Deep Learning Engineer

You will work with large datasets, cutting-edge architectures, and GPU-accelerated training pipelines to build scalable, production-ready deep learning solutions.

Responsibilities

• Design, train, and optimise deep learning models for tasks such as NLP, computer vision, or generative AI.
• Develop high-performance training pipelines, including data pre-processing, augmentation, and batching.
• Conduct experiments, evaluate model performance, and iterate using metrics and validation frameworks.
• Deploy models into production systems using MLOps best practices.

Requirements

• Strong experience with deep learning frameworks (PyTorch, TensorFlow, JAX).
• Proficiency in Python and experience with scientific computing libraries (NumPy, Pandas).
• Experience training and optimising neural networks, including CNNs, RNNs, Transformers, or diffusion models.