1 to 25 of 308 Permanent 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 ...

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 ...

experience in managing, coaching, and developing junior members of a team and wider community. D ESIRABLE : 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 ...

experience in managing, coaching and developing junior members of a team and wider community. D ESIRABLE : 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 ...

several of the following: Commercial experience developing AI or Machine Learning solutions Strong Python development skills Experience with Machine Learning frameworks such as TensorFlow, PyTorch or Scikit-learn Experience with Generative AI technologies including LLMs, LangChain or LlamaIndex Hands-on experience building RAG solutions and working with vector databases Experience ...

/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 ...

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 ...

bring 5+ years of experience in AI, Machine Learning, Data Science, or related fields. Strong Python skills and experience with frameworks such as PyTorch, TensorFlow, and Hugging Face. Experience taking AI proof-of-concepts from idea to production. Strong knowledge of deep learning, NLP, and LLM architectures and experience ...

retrieval systems for operational teams Automated insight generation and decision support What you’ll need Hands‐on experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit‐learn) Strong Python skills for data analysis, modelling, and development Experience working with large language models (LLMs), including prompt engineering, fine‐tuning, and evaluation ...

retrieval systems for operational teams Automated insight generation and decision support What you’ll need Hands‐on experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit‐learn) Strong Python skills for data analysis, modelling, and development Experience working with large language models (LLMs), including prompt engineering, fine‐tuning, and evaluation ...

Community of Practice. Experience Required Essential Strong Python programming and hands‐on experience with core ML/AI libraries (for example scikit‐learn, TensorFlow, PyTorch). Practical experience developing, training and evaluating machine learning, NLP and predictive models. Experience deploying AI/ML in the cloud, particularly Microsoft Azure (Azure ...

concept through to production. Strong technical knowledge, including proficiency in Python and experience with core data science and ML libraries (e.g., scikit‐learn, pandas, PyTorch or TensorFlow). Practical experience with Databricks, including MLflow for experiment tracking and model management, and Spark-based data processing. Familiarity with Generative AI concepts ...

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 ...

parallel and high-throughput file systems (e.g. Everpure, WEKA, VAST, NetApp) sized for training and checkpointing workloads. AI Software, MLOps & Generative AI 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 ...

plus. Solid background in machine learning algorithms, data preprocessing, feature engineering, and model evaluation. Experience with deep learning frameworks like TensorFlow or PyTorch is desirable. Proficiency in handling large datasets, experience with Azure Data Factory, Azure SQL Database, and Cosmos DB. Understanding of CI/CD pipelines, containerization (Docker, Kubernetes ...

technical leadership across the team. What We're Looking For Strong commercial experience developing machine learning solutions using Python. Experience with frameworks such as: PyTorch TensorFlow Scikit-learn XGBoost Experience deploying ML solutions on AWS, including services such as SageMaker, Lambda, and S3. Strong understanding of MLOps tooling, including MLflow ...

token classification. Working knowledge of large language models, including prompting and retrieval-augmented generation (RAG). Experience or coursework in Deep Learning frameworks like PyTorch or TensorFlow. Strong problem‐solving skills and a curiosity for learning new technologies. Good verbal and written communication skills. Familiarity with cloud platforms (e.g., Azure ...

based chatbots and agents Proven ability to build machine learning models and pipelines using Python and common ML and DL libraries (e.g. Pytorch, Tensorflow) from early conceptualisation to full deployment in scalable production environments Ability to design, deploy and maintain ML solutions on modern frameworks to meet functional business requirements ...

lifecycleexpertise: feature engineering, model training,evaluationand production deployment, includingMLOps, 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). Platform & Cloud Engineering Architecture and delivery of scalable cloud data and AI platforms on AWS,Azureor ...

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 ...

model packaging and release management, automated validation, monitoring, and lifecycle management Working knowledge of ML/DL frameworks and tooling (e.g. PyTorch/TensorFlow and the Python ML ecosystem) sufficient to collaborate effectively with data scientists and implement inference pipelines Experience working with complex, multi-layered datasets (including imbalanced data ...

Track record of leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality ...

Broad knowledge of MLOps tooling – for versioning, reproducibility, observability etc. Experience monitoring, maintaining, enhancing existing models over an extended time period Extensive experience with pytorch and related data science python libraries (e.g. pandas) Experience of containerising applications or models for deployment (Docker) Experience with one of the major public cloud ...

with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend systems and data pipelines in a cloud ...

Broad knowledge of MLOps tooling – for versioning, reproducibility, observability etc. Experience monitoring, maintaining, enhancing existing models over an extended time period Extensive experience with PyTorch and related data science Python libraries (e.g. pandas) Experience of containerising applications or models for deployment (Docker) Experience with one of the major public cloud ...