10 of 10 Permanent JAX Jobs in Cambridge

inference, causal reasoning & inference, transfer & multi-task learning, diffusion models, graph neural networks, active learning; Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar; Experience with multi-GPU and distributed training at scale; A team player who thrives in collaborative environments and is committed to enabling colleagues to reach their full potential … physics, or computational biology, or equivalent experience; Experience in developing machine learning models; Very strong programming skills, including experience with Python and deep learning libraries such as PyTorch or JAX; Experience in large-scale distributed optimization of machine learning models across multiple GPUs and nodes. Preferred Qualifications - Familiarity with biological data formats, concepts, and computational models; Experience in cell health More ❯

As a Machine Learning Engineer in the Applied AI team at Graphcore, you will contribute to advancing AI technology by developing and optimising AI models tailored to our specialised hardware. Working closely with the Software development and Research teams, you More ❯

Permanent Role Location : Cambridge Hybrid Policy: 3 days onsite and 2 days working from home weekly Role and Responsibilities As anAI Research Scientist, you will be part of a dynamic team working on next-generation machine learning technologies for real More ❯

About Us Deep Genomics is at the forefront of using artificial intelligence to transform drug discovery. Our proprietary AI platform decodes the complexity of genome biology to identify novel drug targets, mechanisms, and genetic medicines inaccessible through traditional methods. With More ❯

that values innovation, openness, and personal growth Skills & Experience: PhD in Computer Science, Electrical Engineering, or equivalent industry research experience Solid background in machine learning frameworks (PyTorch, TensorFlow, or JAX) Experience in efficient ML techniques: quantization, pruning, distillation Familiarity with deployment on mobile and embedded devices (e.G. Smartphones, mobile CPU/GPU/NPU) Strong skills in Python, C/ More ❯

/EE or related research experience in academia or industry We will consider various levels of experience in relevant research areas Key Skills: Experience with ML frameworks (PyTorch, TensorFlow, JAX) and efficient ML (incl. quantization, pruning, sparsification, distillation, etc.) Experience with deployment on embedded/mobile devices (such as smartphones, with mobile CPU, GPU, NPU) Experience with distributed and multi More ❯

Proven industry experience in machine learning, including deep learning and/or generative models. 3. A working knowledge and practical experience with modern ML frameworks (e.g., PyTorch, TensorFlow, or JAX). Key Words: Machine Learning Scientist/Structure-based Drug Discovery/Protein-Ligand Interaction/Computational Chemistry/AI Techniques/Molecular Modelling/Virtual Screening/Deep Learning More ❯

Machine Learning Scientists/Engineers, Cambridge, UK Astex Pharmaceuticals is a global leader in innovative drug discovery, utilizing its proprietary Fragment-Based Drug Discovery platform to develop new drug candidates, with several progressing in clinical trials. The company focuses on More ❯

modern AI/ML methods (e.g., generative models, GNNs, active learning, foundation models)in a scientific context.- Strong coding skills and experience with relevant ML frameworks(e.g., PyTorch, TensorFlow, JAX) and chemistry toolkits (e.g., RDKit).- Deep understanding of molecular representation techniques and their application in modeling.- Experience in designing and implementing robust, scalable AI-driven workflows and tools.- Passion More ❯

About the role: Join a mission-focused technology consultancy delivering breakthrough AI and machine learning solutions to complex, real-world problems. You will apply your curiosity, creativity, and rigour to design and deploy ML systems across diverse projects, working in More ❯