1 to 25 of 189 DemandTrendPermanent PyTorch Jobs in the UK

collaboration skills Full right to work in the UK (we are unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits: 💰 Competitive Salary More ❯

collaboration skills Full right to work in the UK (we are unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits: 💰 Competitive Salary More ❯

a related field. 6+ years of experience in ML Engineering or Data Science (finance, fintech, or treasury a plus). Proficiency in Python-including pandas, scikit learn, TensorFlow/PyTorch, LightGBM/XGBoost-and experience with SQL. Hands on experience with cloud ML platforms (AWS SageMaker, Azure ML, or Google AI Platform). Solid understanding of software engineering fundamentals: version More ❯

Familiarity with Azure Databricks is a plus. Solid background in machine learning algorithms, data pre-processing, 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), and experience implementing More ❯

and technologies across our products. For this role, we're looking for: Strong Python proficiency with hands-on experience in AI/ML frameworks including RAG, LangChain, TensorFlow, and PyTorch Practical experience with Generative AI and exposure to leading LLM platforms (Anthropic, Meta, Amazon , OpenAI) Proficiency with essential data science libraries including Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and More ❯

Stay up to date with the latest advancements in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps More ❯

Stay up to date with the latest advancements in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps More ❯

Stay up to date with the latest advancements in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps More ❯

Stay up to date with the latest advancements in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps More ❯

Stay up to date with the latest advancements in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps More ❯

techniques (supervised, unsupervised, reinforcement learning). Solid background in data preprocessing, wrangling, and feature engineering. Proficiency in Python (essential) and familiarity with relevant libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Experience with prompt engineering and model evaluation. Deployment experience using Docker or other containerisation tools. Exposure to GPU-based environments for large-scale model training and tuning. Experience with More ❯

techniques (supervised, unsupervised, reinforcement learning). Solid background in data preprocessing, wrangling, and feature engineering. Proficiency in Python (essential) and familiarity with relevant libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Experience with prompt engineering and model evaluation. Deployment experience using Docker or other containerisation tools. Exposure to GPU-based environments for large-scale model training and tuning. Experience with More ❯

techniques (supervised, unsupervised, reinforcement learning). Solid background in data preprocessing, wrangling, and feature engineering. Proficiency in Python (essential) and familiarity with relevant libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Experience with prompt engineering and model evaluation. Deployment experience using Docker or other containerisation tools. Exposure to GPU-based environments for large-scale model training and tuning. Experience with More ❯

RFP process, as preferred bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms – demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools (e.g. Terraform). Technology deployment– proven experience using More ❯

learning modelling techniques and how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they emerge. Experience of using Cloud technologies More ❯

analysis, anomaly detection, forecasting, or Natural Language Processing (NLP). Strong proficiency in Python/R and expertise with AI/ML libraries/frameworks (e.g., scikit-learn, TensorFlow, PyTorch, Keras). Solid understanding of statistical modelling, econometric techniques, data manipulation, and experience with large datasets/distributed computing; familiarity with Generative AI is a plus. Excellent problem-solving, analytical More ❯

production systems. Collaborate with data scientists, engineers, and product teams to define AI solutions. Ensure scalability, performance, and ethical AI practices. Required Skills & Experience: Strong experience in Python, TensorFlow, PyTorch, Scikit-learn or similar frameworks. Solid understanding of machine learning, deep learning, NLP, or computer vision. Hands-on with data engineering, model deployment (MLOps), and cloud platforms (AWS, Azure, GCP More ❯

production systems. Collaborate with data scientists, engineers, and product teams to define AI solutions. Ensure scalability, performance, and ethical AI practices. Required Skills & Experience: Strong experience in Python, TensorFlow, PyTorch, Scikit-learn or similar frameworks. Solid understanding of machine learning, deep learning, NLP, or computer vision. Hands-on with data engineering, model deployment (MLOps), and cloud platforms (AWS, Azure, GCP More ❯

machine learning engineers, AI researchers, and data scientists, driving end-to-end AI solution delivery. Designing and implementing AI architectures across cloud and on-prem environments, leveraging tools like PyTorch, TensorFlow, and Hugging Face. Spearheading the development of production ready AI models, from foundational LLMs to custom built cognitive agents, solving real world business challenges. Establishing scalable ML/AI More ❯

and implementing solutions defined by project leads. Desirable Experience Strong Python expertise. Experience with GNU/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. Experience with CI More ❯

and implementing solutions defined by project leads. Desirable Experience Strong Python expertise. Experience with GNU/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. Experience with CI More ❯

and implementing solutions defined by project leads. Desirable Experience Strong Python expertise. Experience with GNU/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. Experience with CI More ❯

Data Science with reasonable industry experience, or an MS with significant industry or research experience in the field • Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) • Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals • Experience with big More ❯

Strong publication record: publications in top speech and language processing and machine learning conferences and journals Strong Machine Learning Development Skills: Proficient in Python and expert-level understanding of PyTorch and relevant deep learning packages. GPU Computing Experience: Hands-on experience with effectively leveraging GPU hardware for training and inference. DevOps and Cloud Computing Proficiency: Experience with AWS, Azure, or More ❯

of data structures, software architecture, and data modelling, with experience handling diverse datasets (tabular, computer vision, point cloud, game data). Proficient with ML frameworks (NumPy, OpenCV, scikit-learn, PyTorch/PyTorch3D, TensorFlow, Keras). Experience with CI/CD pipelines, version control (GitLab, Perforce), cloud platforms (preferably AWS) and scalable deployment workflows. Outstanding problem-solving and analytical capabilities, coupled More ❯