1 to 25 of 255 JAX Jobs in the UK

pipelines: data collection/cleaning, feature engineering, model training, validation, and inference. Rapidly prototype novel models (eg, neural networks, probabilistic models) using PyTorch, TensorFlow, JAX, or equivalent. Productionize models in cloud/on-prem environments (AWS/GCP/Azure) with containerization (Docker/Kubernetes) and ensure low-latency, high More ❯

the analysis or application of data in finance, economics, or related fields is a plus. • Experience with machine learning libraries such as PyTorch, TensorFlow, JAX is a plus. • Experience applying generative AI solutions (via open source tools or through Azure, Amazon Bedrock, Nvidia etc.) is a plus. • Experience with cloud More ❯

in AI research and applied machine learning. Expertise in key data science technologies and techniques, such as Python, Git, AWS, AWS Sagemaker, PyTorch, TensorFlow, Jax, Numpy, Scikit-learn, Time-series forecasting, Classification, Regression, Large-language models, and Experiment Design. Strong stakeholder management skills and the ability to communicate complex ideas More ❯

in AI research and applied machine learning. Expertise in key data science technologies and techniques, such as Python, Git, AWS, AWS Sagemaker, PyTorch, TensorFlow, Jax, Numpy, Scikit-learn, Time-series forecasting, Classification, Regression, Large-language models, and Experiment Design. Strong stakeholder management skills and the ability to communicate complex ideas More ❯

in AI research and applied machine learning. Expertise in key data science technologies and techniques, such as Python, Git, AWS, AWS Sagemaker, PyTorch, TensorFlow, Jax, Numpy, Scikit-learn, Time-series forecasting, Classification, Regression, Large-language models, and Experiment Design. Strong stakeholder management skills and the ability to communicate complex ideas More ❯

in AI research and applied machine learning. Expertise in key data science technologies and techniques, such as Python, Git, AWS, AWS Sagemaker, PyTorch, TensorFlow, Jax, Numpy, Scikit-learn, Time-series forecasting, Classification, Regression, Large-language models, and Experiment Design. Strong stakeholder management skills and the ability to communicate complex ideas More ❯

such as computational pathology, genomics, transcriptomics or medical imaging. Strong experience with Python and at least one deep learning frameworks such as PyTorch, TensorFlow, JAX, and PyTorch Lightning. Familiarity with packages and technologies such as NumPy, Pandas, Scikit-learn, Scikit-image, OpenCV, Git, and Bash. Experience working with HPC clusters More ❯

of relevant working experience - Experience with machine learning fundamentals, with working knowledge of Python and experience with deep learning frameworks such as Pytorch, TensorFlow, JAX or MXNet - 3+ years of relevant experience in developing and deploying large scale machine learning or deep learning models and/or systems into production More ❯

versioning, testing, CI/CD, API design, MLOps) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., PyTorch, MLFlow, JAX) Distributed computing frameworks (e.g., Spark, Dask) Cloud platforms (e.g., AWS, Azure, GCP) and HP computing Containerization and orchestration (Docker, Kubernetes) Ability to scope and effectively More ❯

Optimization context (Gaussian processes, Bayesian Neural Networks) on small and large datasets. Strong experience in at least one ML framework (PyTorch/TensorFlow/Jax) and robust experience in Python data science ecosystem (Numpy, SciPy, Pandas, etc.) Experience using a cloud computing service to reduce runtime to train and evaluate More ❯

a quantitative field (e.g., Computer Science, Machine Learning, Statistics, Physics, Mathematics) or equivalent industry experience. Strong background in deep learning frameworks (e.g., PyTorch, TensorFlow, JAX). Experience with distributed computing platforms (AWS, GCP, Azure, or on-prem clusters). Ideal: Kubernetes and Docker experience for scalable, reproducible workflows. Working at More ❯

. Knowledge of linear algebra, calculus and statistics equivalent to at least first-year university coursework. Experience exploring, analysing and visualising data. Experience using Jax, PyTorch, TensorFlow, NumPy, Pandas or similar ML/scientific libraries. In addition, the following would be an advantage: Experience with frontier LLM development. Experience collaborating More ❯

scaler platforms, e.g., AWS, Azure, GCP); building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications; C/C++ for computer vision, geometry processing, or scientific computing; software engineering concepts and best practices (e.g., versioning, testing More ❯

complex ideas clearly Preferred: Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) A strong publication record in top conferences (e.g., NeurIPS, ICML, ICLR, ACL) Why Join Us Work on groundbreaking AI research with real-world applications and More ❯

complex ideas clearly Preferred: Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) A strong publication record in top conferences (e.g., NeurIPS, ICML, ICLR, ACL) Why Join Us Work on groundbreaking AI research with real-world applications and More ❯

complex ideas clearly Preferred: Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) A strong publication record in top conferences (e.g., NeurIPS, ICML, ICLR, ACL) Why Join Us Work on groundbreaking AI research with real-world applications and More ❯

complex ideas clearly Preferred: Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) A strong publication record in top conferences (e.g., NeurIPS, ICML, ICLR, ACL) Why Join Us Work on groundbreaking AI research with real-world applications and More ❯

complex ideas clearly Preferred: Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) A strong publication record in top conferences (e.g., NeurIPS, ICML, ICLR, ACL) Why Join Us Work on groundbreaking AI research with real-world applications and More ❯

complex ideas clearly Preferred: Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) A strong publication record in top conferences (e.g., NeurIPS, ICML, ICLR, ACL) Why Join Us Work on groundbreaking AI research with real-world applications and More ❯

complex ideas clearly Preferred: Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) A strong publication record in top conferences (e.g., NeurIPS, ICML, ICLR, ACL) Why Join Us Work on groundbreaking AI research with real-world applications and More ❯

complex ideas clearly Preferred: Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) A strong publication record in top conferences (e.g., NeurIPS, ICML, ICLR, ACL) Why Join Us Work on groundbreaking AI research with real-world applications and More ❯

learning, and/or large language models (LLMs) •Experience in chip design and applied AI research •Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) Why Join Us •Work on groundbreaking AI research with real-world applications and a strong commitment to open-source contributions and scientific advancement •Collaborate with More ❯

MLOps practices and tools including version control, automated testing, and CI/CD. Experience in at least one ML framework (PyTorch/TensorFlow/Jax) and robust experience in the Python data science ecosystem. Experience with large language models (e.g. autoregressive LLMs) for biological sequences is a plus. Familiarity with More ❯

in Machine Learning and Deep Learning, with exposure to Reinforcement Learning as a plus. Proficiency in Python and modern ML libraries (e.g., TensorFlow, PyTorch, JAX, or Keras). Experience with version control systems (GitHub, GitLab) and knowledge of clean, maintainable coding practices. Familiarity with CI/CD pipelines for automating More ❯

in Machine Learning and Deep Learning, with exposure to Reinforcement Learning as a plus. Proficiency in Python and modern ML libraries (e.g., TensorFlow, PyTorch, JAX, or Keras). Experience with version control systems (GitHub, GitLab) and knowledge of clean, maintainable coding practices. Familiarity with CI/CD pipelines for automating More ❯