1 to 25 of 631 PyTorch Jobs in England

quality assessment. Good foundation in statistics, probability, optimization, experimentation, and applied machine learning. Advanced proficiency in Python and modern AI frameworks, including PyTorch, TensorFlow, Scikit-Learn, Hugging Face, LangChain, Semantic Kernel, and related ecosystems. Experience building and scaling enterprise AI platforms, ML infrastructure, and intelligent applications serving thousands of users. ...

quality assessment**.* Good foundation in **statistics, probability, optimization, experimentation, and applied machine learning**.* Advanced proficiency in Python and modern AI frameworks, including **PyTorch, TensorFlow, Scikit-Learn, Hugging Face, LangChain, Semantic Kernel, and related ecosystems**.* Experience building and scaling **enterprise AI platforms, ML infrastructure, and intelligent applications serving ...

responsible AI principles, model interpretability, and ethical considerations. Strong interpersonal skills and team working. DESIRABLE: Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage ...

bring experience in managing, coaching and developing junior members of a team and wider community. DESIRABLE: Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g. GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage ...

Learning, predictive modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous agent systems, building ...

Learning, predictive modelling and applied AI , developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous ...

Learning, predictive modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous ...

Learning, predictive modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous ...

Learning, predictive modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous ...

Learning, predictive modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous ...

VAST, NetApp) sized for training and checkpointing workloads.AI Software, MLOps & Generative AIOrchestration & containers: Kubernetes, Docker, Slurm, Run:ai or equivalent GPU scheduling platforms.ML frameworks: PyTorch and TensorFlow at a working, hands-on level.Distributed training: Horovod, DeepSpeed, Megatron-LM, or equivalent multi-node training frameworks.Inference & serving: NVIDIA Triton, vLLM, TensorRT ...

Skills & Experience: Experience in machine learning, data science, or applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure, or GCP) and ML pipelines. Ability to analyse ...

Skills & Experience: Experience in machine learning, data science, or applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure, or GCP) and ML pipelines. Ability to analyse ...

/fairness and emerging regulations. Machine Learning Mastery – profound understanding of ML principles, algorithms, frameworks, and training pipelines. Technical Proficiency – programming in Python, TensorFlow, PyTorch or similar; modern LLM/agent frameworks; cloud AI platforms (Amazon Bedrock, Azure OpenAI/AI Foundry, Google Vertex AI); vector databases; containerization and orchestration ...

Skills & Experience: Experience in machine learning, data science, or applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure, or GCP) and ML pipelines. Ability to analyse ...

Language Model (LLM) powered solutions and generative AI applications at enterprise scale. Strong Python development skills, with experience using machine learning frameworks such as PyTorch, TensorFlow, and Scikit-learn. Deep understanding of AI Engineering, MLOps practices, and modern LLM technologies, including prompt engineering, Retrieval-Augmented Generation (RAG), AI agents ...

Language Model (LLM) powered solutions and generative AI applications at enterprise scale. Strong Python development skills, with experience using machine learning frameworks such as PyTorch, TensorFlow, and Scikit‐learn. Deep understanding of AI Engineering, MLOps practices, and modern LLM technologies, including prompt engineering, Retrieval‐Augmented Generation (RAG), AI agents ...

lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit‐learn, PyTorch, XGBoost) and cloud‐native ML services (SageMaker, Azure ML, Vertex AI). Architecture and delivery of scalable cloud data and AI platforms on AWS, Azure ...

stack. Experience with Azure OpenAI Service, Azure AI Foundry, Azure Machine Learning or related Azure AI services.AI engineering tools. Familiarity with frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, LangChain or LlamaIndex, and with vector databases or semantic search.Full-stack delivery. Exposure to Docker, CI/CD, REST APIs ...

implement models, optimize performance, and manage training pipelines effectively.• Technical Proficiency: Proficiency in programming languages commonly used in AI development, such as Python, TensorFlow, PyTorch, or similar tools, along with modern LLM/agent frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen). Experience with cloud AI platforms (e.g., Amazon ...

research and evaluate applicability to client projects Requirements 5+ years of experience in machine learning engineering or applied ML research Strong proficiency in Python, PyTorch or TensorFlow, and Scikit-learn Experience deploying ML models at scale using Docker, Kubernetes, or serverless Deep understanding of ML fundamentals: optimisation, regularisation, evaluation metrics ...

experience with classical NLP techniques (BERT, topic modelling, summarisation), statistical analysis, and knowledge graphs. Deep Learning: Familiarity or experience with Deep Learning (TensorFlow, PyTorch). Benefits Package and Benefits: Competitive Salary Bonus Scheme Private Healthcare Insurance 25 Days Annual Leave + Bank Holidays Up to 10 days allocated for development ...

experience with classical NLP techniques (BERT, topic modelling, summarisation), statistical analysis, and knowledge graphs. Deep Learning: Familiarity or experience with Deep Learning (TensorFlow, PyTorch). What We Offer: Competitive Salary Bonus Scheme Private Healthcare Insurance 25 Days Annual Leave + Bank Holidays Up to 10 days allocated for development training ...

lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit-learn, PyTorch, XGBoost) and cloud-native ML services (SageMaker, Azure ML, Vertex AI). Software Engineering: Production-grade Python services (FastAPI, AWS Lambda, event-driven patterns ...

GitHub, Docker/Kubernetes, MLflow, Jira. Edge deployments: Nvidia Jetson (e.g. AGX Orin), Raspberry Pi, or other embedded accelerators. Distributed model training & infra: Pytorch DDP, FDSP and TorchTitan, Megatron, Slurm, Run:ai, DeepSpeed, Kubernetes, cloud or on‐prem GPU clusters. About you You’ve built ML systems that persist—deployed ...