16 of 16 Remote/Hybrid PyTorch Jobs in Edinburgh

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 ...

data. Experience with retrieval systems for agents: retrieval-augmented generation, embedding models, vector databases, and long-term memory. Experience with machine learning libraries (e.g. PyTorch, Tensorflow), cloud platforms (AWS, Azure, GCP), and the analysis of financial or economic data. Experience helping define technical standards, best practices, or ways of working ...

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 ...

Need... Confirmed experience in leading data science projects in cybersecurity, fraud, or behavioural analytics. Data Engineering - Deep expertise in Python, ML frameworks (e.g. TensorFlow, PyTorch), and cloud platforms (preferably GCP). Deep Learning Theory & Applications - Strong grasp of anomaly detection, time-series modelling, and deep learning architectures. Experience with LLMs ...

need...Confirmed experience in leading data science projects in cybersecurity, fraud, or behavioural analytics. Data Engineering - Deep expertise in Python, ML frameworks (e.g. TensorFlow, PyTorch), and cloud platforms (preferably GCP). Deep Learning Theory & Applications - Strong grasp of anomaly detection, time-series modelling, and deep learning architectures. Experience with LLMs ...

experimentation, observability, debugging, and testing approaches for AI/ML systems, including non-deterministic and agentic applications. Machine learning and optimization frameworks such as PyTorch, TensorFlow, or JAX. Distributed systems, cloud infrastructure, model serving, orchestration, data pipelines, and API design. Performance optimization across latency, throughput, compute utilization, reliability, scalability ...

experimentation, observability, debugging, and testing approaches for AI/ML systems, including non-deterministic and agentic applications. Machine learning and optimization frameworks such as PyTorch, TensorFlow, or JAX. Distributed systems, cloud infrastructure, model serving, orchestration, data pipelines, and API design. Performance optimization across latency, throughput, compute utilization, reliability, scalability ...

systems at scale, including model lifecycle security, data pipelines, and secure deployment. Strong hands‐on experience with machine learning stacks, such as PyTorch, TensorFlow, MLflow, Kubeflow, or equivalent managed platforms (e.g. Vertex AI, Azure ML). Solid understanding of cloud‐native and containerised architectures, including Kubernetes and serverless technologies. Experience ...

systems at scale, including model lifecycle security, data pipelines, and secure deployment.Strong hands‐on experience with machine learning stacks, such as PyTorch, TensorFlow, MLflow, Kubeflow, or equivalent managed platforms (e.g. Vertex AI, Azure ML).Solid understanding of cloud‐native and containerised architectures, including Kubernetes and serverless technologies.Experience operating in complex ...

candidates with the following technical skills:Industry experience working on Agile projects across the full software life cycle.Proficiency in machine learning frameworks such as PyTorch and TensorFlow, as well as tools for model integration.A strong foundation in AI/ML, including transformer architectures, tokenisation, embeddings, and fine-tuning large language ...

Object Detection and LLM analysis implementation Machine Learning & AI Libraries including: Transformers/Hugging Face for working with pre-trained LLMs, finetuning, and inference PyTorch for deep learning model development and training OpenCV for computer vision tasks and image preprocessing in object detection PIL/Pillow for image manipulation ...

systems at scale, including model lifecycle security, data pipelines, and secure deployment. Strong hands‐on experience with machine learning stacks, such as PyTorch, TensorFlow, MLflow, Kubeflow, or equivalent managed platforms (e.g. Vertex AI, Azure ML). Solid understanding of cloud‐native and containerised architectures, including Kubernetes and serverless technologies. Experience ...

boost AI model inference performance on CPU and CPU/XPU hybrid systems, using advanced compiler techniques. You will profile frameworks such as TensorFlow, PyTorch and ONNX, optimize graph execution, and contribute to open research with practical insights and publications. #J-18808-Ljbffr ...