101 to 125 of 390 PyTorch Jobs in the UK

learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work cross-functionally with marketing, CRM More ❯

learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work cross-functionally with marketing, CRM More ❯

learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work cross-functionally with marketing, CRM More ❯

learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work cross-functionally with marketing, CRM More ❯

learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work cross-functionally with marketing, CRM More ❯

learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work cross-functionally with marketing, CRM More ❯

solutions independently. Ideal Experience 5+ years in applied Machine Learning, with significant hands-on NLP project experience. Deep understanding of transformer models and LLM fine-tuning. Proficient in Python, PyTorch or TensorFlow, and scikit-learn. Practical experience deploying ML models in production environments (cloud-native or on-prem). Familiar with data versioning, MLflow, and monitoring frameworks (e.g. Weights & Biases More ❯

Working with Data Scientists to deploy trained machine learning models into production environments Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch Experience with software engineering best practices and developing applications in Python. Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one of the 3 major cloud More ❯

Working with Data Scientists to deploy trained machine learning models into production environments Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch Experience with software engineering best practices and developing applications in Python. Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one of the 3 major cloud More ❯

Working with Data Scientists to deploy trained machine learning models into production environments Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch Experience with software engineering best practices and developing applications in Python. Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one of the 3 major cloud More ❯

Working with Data Scientists to deploy trained machine learning models into production environments Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch Experience with software engineering best practices and developing applications in Python. Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one of the 3 major cloud More ❯

sequential (e.g. sensor time-series) data and decision-making post PhD Experience in software development for proof of concept in Python Experience with machine and deep learning frameworks: TensorFlow, PyTorch, scikit-learn, etc. Of particular interest are candidates with experience in one or more of the following domains: RF communications and CEMA Electronic or Electromagnetic Warfare (EW) Tracking and sensor More ❯

in Artificial Intelligence. Skills, Knowledge, and Experience Technical proficiency You write production-grade, scalable Python code, ensuring that your models are robust, maintainable, and optimised for performance. Comfortable with PyTorch Knowledge of Transformer-based models Knowledge of Large Language Models (LLMs) Proven experience of having delivered successful machine learning projects into production Strong understanding of software development fundamentals, in particular More ❯

BASIC QUALIFICATIONS - 5+ years of hands-on experience optimizing AI infrastructure, with deep expertise in inference acceleration frameworks (e.g., vLLM, SGLang, TensorRT, etc.), model training and serving systems across PyTorch and TensorFlow ecosystems; - Advanced proficiency in Nvidia GPU performance optimization techniques, including memory management, kernel fusion, and quantization strategies for large-scale deep learning workloads; - Strong foundation in parallel computing More ❯

PhD in Computer Science, Machine Learning or related discipline 3+ years’ experience developing ML models, with a strong focus on medical imaging Proven track record using deep learning frameworks (PyTorch/TensorFlow) Solid Python skills and familiarity with cloud or MLOps tools (Docker, Kubernetes, MLFlow) Understanding of data pipelines and image analysis techniques (segmentation, registration, feature extraction) Benefits Share options More ❯

PhD in Computer Science, Machine Learning or related discipline 3+ years’ experience developing ML models, with a strong focus on medical imaging Proven track record using deep learning frameworks (PyTorch/TensorFlow) Solid Python skills and familiarity with cloud or MLOps tools (Docker, Kubernetes, MLFlow) Understanding of data pipelines and image analysis techniques (segmentation, registration, feature extraction) Benefits Share options More ❯

product teams Optimise big data and cloud infrastructure (Azure/GCP) Requirements: 3+ years in data engineering or MLOps Strong Python and exposure to ML/AI libraries (e.g. PyTorch, HuggingFace) Proficient with Airflow, DBT, Docker, Kubernetes Cloud deployment experience (Azure preferred) Backend/API development experience with client-facing exposure Interested? Please apply below. More ❯

frameworks (e.g., Flask, Django) Ability to work autonomously in an early-stage environment Strong problem-solving and collaboration abilities Nice-to-haves Background in machine learning/AI frameworks (PyTorch, transformers, etc.) Familiarity with cloud infrastructure (GCP, AWS) and CI/CD (GitHub Actions) Experience with SQLAlchemy, Flask and PyQt (or other GUI frameworks) Why join Nodko Shape the foundation More ❯

frameworks (e.g., Flask, Django) Ability to work autonomously in an early-stage environment Strong problem-solving and collaboration abilities Nice-to-haves Background in machine learning/AI frameworks (PyTorch, transformers, etc.) Familiarity with cloud infrastructure (GCP, AWS) and CI/CD (GitHub Actions) Experience with SQLAlchemy, Flask and PyQt (or other GUI frameworks) Why join Nodko Shape the foundation More ❯

frameworks (e.g., Flask, Django) Ability to work autonomously in an early-stage environment Strong problem-solving and collaboration abilities Nice-to-haves Background in machine learning/AI frameworks (PyTorch, transformers, etc.) Familiarity with cloud infrastructure (GCP, AWS) and CI/CD (GitHub Actions) Experience with SQLAlchemy, Flask and PyQt (or other GUI frameworks) Why join Nodko Shape the foundation More ❯

frameworks (e.g., Flask, Django) Ability to work autonomously in an early-stage environment Strong problem-solving and collaboration abilities Nice-to-haves Background in machine learning/AI frameworks (PyTorch, transformers, etc.) Familiarity with cloud infrastructure (GCP, AWS) and CI/CD (GitHub Actions) Experience with SQLAlchemy, Flask and PyQt (or other GUI frameworks) Why join Nodko Shape the foundation More ❯

frameworks (e.g., Flask, Django) Ability to work autonomously in an early-stage environment Strong problem-solving and collaboration abilities Nice-to-haves Background in machine learning/AI frameworks (PyTorch, transformers, etc.) Familiarity with cloud infrastructure (GCP, AWS) and CI/CD (GitHub Actions) Experience with SQLAlchemy, Flask and PyQt (or other GUI frameworks) Why join Nodko Shape the foundation More ❯

communicator across technical teams and stakeholders Effective problem-solver who takes initiative in complex production settings Experience with scientific computing, deep learning, big data, or health IT ontologies (e.g., PyTorch, JAX, Spark, HL7, FHIR) (desirable) Familiarity with cloud infrastructure (Azure/AWS), infrastructure as code, Kubernetes, Linux, Docker, data pipelines, and MLOps tools (desirable) Passion for biomedical topics and startup More ❯

communicator across technical teams and stakeholders Effective problem-solver who takes initiative in complex production settings Experience with scientific computing, deep learning, big data, or health IT ontologies (e.g., PyTorch, JAX, Spark, HL7, FHIR) (desirable) Familiarity with cloud infrastructure (Azure/AWS), infrastructure as code, Kubernetes, Linux, Docker, data pipelines, and MLOps tools (desirable) Passion for biomedical topics and startup 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 ❯