Deep Learning Engineer

Key Responsibilities

• Develop and train deep learning models using frameworks such as PyTorch or TensorFlow.
• Preprocess and augment datasets to improve model robustness and generalization.
• Design and run experiments, including model evaluation, hyperparameter tuning, and performance benchmarking.
• Optimize models for deployment (quantization, pruning, ONNX conversion, etc.).
• Collaborate with data engineers, product owners, and domain experts to define and meet project goals.
• Contribute to documentation and code reviews to ensure reproducibility and code quality.

Required Skills

• Strong proficiency in Python and deep learning libraries (PyTorch, TensorFlow, Keras).
• Experience with CNNs, RNNs, Transformers, or other modern architectures.
• Solid understanding of ML lifecycle: data preprocessing, training, evaluation, and deployment.
• Familiarity with tools such as Docker, Git, Jupyter, and MLflow or Weights & Biases.
• Experience deploying models to production (e.g., using REST APIs, edge devices, or cloud platforms).
• Ability to work independently and communicate effectively with remote teams.

Preferred Qualifications

• M.Sc. or Ph.D. in Computer Science, AI, Data Science, or a related field.
• Experience with domain-specific data (e.g., medical imaging, time-series, NLP, LLMs).
• Prior freelance or consultancy experience with international teams.
• Based in Norway or able to work within CET business hours.