226 to 250 of 785 PyTorch Jobs in England

AI governance and risk Required Skills & Experience Production experience with Generative AI, LLMs, NLP, and RAG systems Strong knowledge of Knowledge Graphs and semantic technologies Proficient in Python, SQL, PyTorch/TensorFlow Experience with DevOps, CI/CD, DevSecOps and secure ML pipelines. Proven experience in AI/ML/Data science leadership with measurable business impact. Degree in Computer More ❯

instruments, derivatives, and risk management principles, with experience applying ML in trading, pricing, or risk analytics contexts. Technical Proficiency - Expert in Python and familiar with ML frameworks such as PyTorch, TensorFlow, and JAX. Skilled in using tools like scikit-learn, XGBoost, and LightGBM. Data Engineering & Infrastructure Skills - Comfortable working with big data technologies (Spark, Dask), SQL/NoSQL databases, and More ❯

domain trends. Skills & Experience: - Demonstrated hands-on experience building production AI/LLM applications. - Strong Python, API design, asynchronous programming, and integration skills. - Experience with ML/LLM frameworks (PyTorch, TensorFlow, scikit-learn, LangChain/LangGraph, LlamaIndex). - Familiarity with cloud deployment (Azure), CI/CD, Infrastructure as Code, and MLOps best practices. - Knowledge of databases, vector search, and knowledge More ❯

domain trends. Skills & Experience: - Demonstrated hands-on experience building production AI/LLM applications. - Strong Python, API design, asynchronous programming, and integration skills. - Experience with ML/LLM frameworks (PyTorch, TensorFlow, scikit-learn, LangChain/LangGraph, LlamaIndex). - Familiarity with cloud deployment (Azure), CI/CD, Infrastructure as Code, and MLOps best practices. - Knowledge of databases, vector search, and knowledge More ❯

domain trends. Skills & Experience: - Demonstrated hands-on experience building production AI/LLM applications. - Strong Python, API design, asynchronous programming, and integration skills. - Experience with ML/LLM frameworks (PyTorch, TensorFlow, scikit-learn, LangChain/LangGraph, LlamaIndex). - Familiarity with cloud deployment (Azure), CI/CD, Infrastructure as Code, and MLOps best practices. - Knowledge of databases, vector search, and knowledge More ❯

domain trends. Skills & Experience: - Demonstrated hands-on experience building production AI/LLM applications. - Strong Python, API design, asynchronous programming, and integration skills. - Experience with ML/LLM frameworks (PyTorch, TensorFlow, scikit-learn, LangChain/LangGraph, LlamaIndex). - Familiarity with cloud deployment (Azure), CI/CD, Infrastructure as Code, and MLOps best practices. - Knowledge of databases, vector search, and knowledge More ❯

domain trends. Skills & Experience: - Demonstrated hands-on experience building production AI/LLM applications. - Strong Python, API design, asynchronous programming, and integration skills. - Experience with ML/LLM frameworks (PyTorch, TensorFlow, scikit-learn, LangChain/LangGraph, LlamaIndex). - Familiarity with cloud deployment (Azure), CI/CD, Infrastructure as Code, and MLOps best practices. - Knowledge of databases, vector search, and knowledge More ❯

and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings into actionable insights for coaches More ❯

and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings into actionable insights for coaches More ❯

and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings into actionable insights for coaches More ❯

and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings into actionable insights for coaches More ❯

and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings into actionable insights for coaches More ❯

ML jobs, including the use of IAC to build data pipelines Expert knowledge of Python. An excellent knowledge of basic machine learning libraries, such as NumPy, SciPy, Pandas, Dask, PyTorch, Tensorflow, etc. A proven track record of linking data from multiple systems for scalable productionised solutions with security and monitoring best practices. Experienced with Cloud Security best practices. Hands-on More ❯

ML jobs, including the use of IAC to build data pipelines Expert knowledge of Python. An excellent knowledge of basic machine learning libraries, such as NumPy, SciPy, Pandas, Dask, PyTorch, Tensorflow, etc. A proven track record of linking data from multiple systems for scalable productionised solutions with security and monitoring best practices. Experienced with Cloud Security best practices. Hands-on More ❯

managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able More ❯

managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able More ❯

managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able More ❯

managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able More ❯

managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able More ❯

managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able More ❯

managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able More ❯

managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able More ❯

managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able More ❯

managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able More ❯

managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able More ❯