12 of 12 Google JAX Jobs in the City of London

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 More ❯

e.g., PyTorch, TensorFlow) Solid grasp of ML techniques; independent and team-oriented mindse Preferred: Experience in LLMs, reinforcement learning, or chip design Familiarity with JAX and optimization frameworks Why Join Us: Work on impactful AI research with real-world applications Collaborate with top researchers in a global team Flexible More ❯

e.g., PyTorch, TensorFlow) Solid grasp of ML techniques; independent and team-oriented mindse Preferred: Experience in LLMs, reinforcement learning, or chip design Familiarity with JAX and optimization frameworks Why Join Us: Work on impactful AI research with real-world applications Collaborate with top researchers in a global team Flexible More ❯

both a scientist and an engineer: excited by innovation, and pragmatic about delivering impact! 🛠️ Key Technologies: Python and modern ML libraries (e.g. PyTorch, TensorFlow, JAX) AWS and cloud infrastructure for scalable training and inference ML ops tooling, model monitoring, and data pipelines Bonus: experience with LLMs & generative AI is More ❯

grasp of computer-architecture fundamentals: memory systems, interconnects, queuing theory, Amdahl/Gustafson analysis. Familiarity with machine-learning workloads and common frameworks (PyTorch, TensorFlow, JAX). Comfort reading RTL or schematics and discussing micro-architectural trade-offs with hardware designers. Excellent data-visualisation and communication skills: able to turn More ❯

grasp of computer-architecture fundamentals: memory systems, interconnects, queuing theory, Amdahl/Gustafson analysis. Familiarity with machine-learning workloads and common frameworks (PyTorch, TensorFlow, JAX). Comfort reading RTL or schematics and discussing micro-architectural trade-offs with hardware designers. Excellent data-visualisation and communication skills: able to turn More ❯

grasp of computer-architecture fundamentals: memory systems, interconnects, queuing theory, Amdahl/Gustafson analysis. Familiarity with machine-learning workloads and common frameworks (PyTorch, TensorFlow, JAX). Comfort reading RTL or schematics and discussing micro-architectural trade-offs with hardware designers. Excellent data-visualisation and communication skills: able to turn More ❯

LLM-based products (GPT, Llama, Mistral, or similar) or conversational AI systems into production. Deep knowledge of modern ML/NLP frameworks (PyTorch, TensorFlow, JAX) and orchestration stacks (LangChain, LlamaIndex, vector databases). Proven track record driving AI governance, model risk management, and compliance within regulated sectors (healthcare, med More ❯

collaborating across functions, especially with engineering, hardware, and system design teams Solid programming and prototyping skills using modern deep learning frameworks (e.g. PyTorch, TensorFlow, JAX) Location: London (hybrid, with 4 days onsite and flexible hours) This is a high-impact role for someone who thrives on building ambitious technology More ❯

role is responsible for designing scalable and intelligent cloud-native architectures that enhance personalization, product discovery, and operational efficiency for major retail customers using Google Cloud technologies. Key Responsibilities: • Architect retail-centric solutions on GCP that optimize customer experience, supply chain, and omnichannel engagement. • Implement and optimize vector search … LangChain, or custom agent orchestration solutions). • Strong understanding of retail data ecosystems, POS integration, and customer engagement analytics. • Strong hands-on experience with Google Cloud Platform (GCP) AI/ML services, especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store). • Proficiency in Python and strong experience with … AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face Transformers). • Experience with data engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid understanding of core AI/ML concepts, including deep learning, neural networks, NLP, and machine learning More ❯

Compiler Engineers to join the team building the ML backend (compiler, run-time, and debugger) for our next-generation OPTUs that connect PyTorch, Tensorflow, JAX, and MXNet down to our low-level kernel drivers.Your mission will be to create seamless support for a broad ecosystem of large AI models … impact technical and business milestones that drive the success of Flux. Architect & Build: Design and implement our compiler, runtime, and debugger for PyTorch, TensorFlow, JAX, and MXNet on custom hardware. Optimise Performance: Apply advanced techniques (layout, fusion, scheduling, tiling) to eliminate bottlenecks and maximise throughput. Mentor & Encourage Standards: Lead … C/C++ programming. Deep expertise in ML framework internals, compilers, low-level programming, and optimisation techniques. Deep expertise in optimising Tensorflow, PyTorch or JAX deep learning models. Deep expertise with multiple toolchains like LLVM, OpenXLA/XLA, MLIR, TVM. Practical experience applying machine learning in high-performance computing More ❯

to architect and build the ML backend (compiler, run-time, and debugger) for our next-generation OPTUs. You will own integration with PyTorch, Tensorflow, JAX, and MXNet down to our low-level kernel drivers. Your mission will be to create seamless support for a broad ecosystem of large AI … ensure software and hardware are designed together to deliver maximum performance. Architect & Build: Design and implement our compiler, runtime, and debugger for PyTorch, TensorFlow, JAX, and MXNet on custom hardware. Optimize Performance: Apply advanced techniques (layout, fusion, scheduling, tiling) to eliminate bottlenecks and maximize throughput. Mentor & Define Standards: Lead … on C/C++ programming. Extensive experience in ML framework internals, compilers, low-level programming, and optimisation techniques. Extensive experience optimising Tensorflow, PyTorch or JAX deep learning models. Extensive experience with multiple toolchains like LLVM, OpenXLA/XLA, MLIR, TVM. Practical experience applying machine learning in high-performance computing More ❯