Amazon★3.5 (56k)· London

Develop generative AI and large models using Java, C++, Python, and Unix/Linux for Prime Video’s observability team, which combines log management, tracing, and AI-powered analytics to detect and diagnose issues at unprecedented speed.

You'll work with NLP, LLMs, PyTorch, Hugging Face, and Python on problems in semantic chunking, information extraction, knowledge graph construction, and retrieval optimisation. You'll join an AI research organisation building the document understanding layer that powers next-generation AI search and reasoning systems.

Microsoft★4.2 (9k)· London

Works with Python, PyTorch and retrieval technologies including ColBERT, SPLADE, dense/sparse hybrid, RAG and LLM-integrated architectures. Builds state-of-the-art retrieval systems for Microsoft 365 Copilot Search, Chat and Agent experiences, serving millions of enterprise users daily.

Amazon★3.5 (56k)· London

As an Applied Science Intern, you will work with machine learning, deep learning, generative AI, large language models, speech technology, robotics, computer vision, optimization, operations research, quantum computing, and formal methods, using Java, C++, or Python. You will design and develop end-to-end systems, working with Amazon scientists to create algorithms and models that are deployed into production.

Amazon★3.5 (56k)· London

You will work with Java, C++, Python, neural deep learning, machine learning, TensorFlow, PyTorch, Spark, and formal methods (model checking, interactive theorem proving, property-based testing). The Agentic Automated Reasoning Group builds next-generation software verification tools combining AI and cloud computing to analyze code—from Infrastructure as Code to assembly—for provable security, availability, and correctness across AWS services.

Amazon★3.5 (56k)· London

Develops personalised recommendations using Java, C++, Python, neural deep learning, and tools like TensorFlow, Spark, and MLLib. The Prime Video Insights team builds observability features that reduce customer-impact time, consuming petabytes of data daily for internal builders.

Thomson Reuters★3.9 (4.3k)· London

You'll work with PyTorch, JAX, HuggingFace Transformers, vLLM, LLM APIs, Ray, Spark, and experiment tracking tools like Weights & Biases and MLflow on Thomson Reuters' Foundational Research division, which develops advanced algorithms and training techniques for Large Language Models including LLM training, post-training techniques for reasoning and workflows, data-centric ML, and evaluation. You'll design and implement scalable systems for training, fine-tuning, and evaluating LLMs while translating cutting-edge research into production implementations.

Boston Consulting Group★4.2 (537)· London

You'll develop testing and evaluation frameworks for generative AI and AI products using Python, PyTorch, and TensorFlow, ensuring they meet responsible AI standards for safety, security, and equity. The Responsible AI team at BCG X—a 3,000-person tech organization within the consulting firm—supports product teams across industries in building trustworthy AI systems throughout the software development lifecycle. The role requires 3-5+ years in responsible AI, 3+ years with generative AI models, and program/project management experience.