6 of 6 Remote/Hybrid PyTorch Jobs in Glasgow

used for AI/ML development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible ...

Python, R), with hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation ...

similar programming languages used for AI and data engineering, with hands-on experience building production-grade solutions.Experience with machine learning frameworks and tools (e.g., PyTorch, TensorFlow, scikit-learn) and practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation ...

/ML and Generative AI solutions; evidence of real-world impact highly desirable.Expert-level proficiency in Python, and modern AI/ML frameworks, including PyTorch, TensorFlow, and specialised Generative AI libraries (LangChain, LangGraph or related open-source toolkits strongly preferred. Background in Traditional ML/AI is preferred.Deep understanding ...

another modern programming language used for data science and machine learning development.Practical experience with machine learning frameworks and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring and optimisation.Understanding of MLOps ...

5+ years (Senior) or 8+ years (Staff) of hands‐on applied ML experience, including production‐grade work. Deep familiarity with modern deep learning stack (PyTorch or JAX), and breadth across at least two of: generative models (diffusion, autoregressive, flow‐based), graph and equivariant networks, vision (CNNs, ViTs, multimodal LLMs), search ...