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 will work with Python/C++, Ray, Spark, Flink, Kafka/Beam, and ML frameworks for search/recsys and frontier AI (LLMs, RL, multi-agent orchestration). Your role involves building enterprise superintelligence systems—end-to-end architectures that take ownership of business outcomes—as a founding scientist on a small, senior team.

Amazon★3.5 (56k)· London

You'll use Java, C++, or Python and AI coding assistants to build and ship real-time machine learning models for ranking, valuing, and bidding ads on Amazon's Demand-Side Platform. The team aims to make ads more relevant for shoppers while balancing advertiser and Amazon objectives, working across Edinburgh and London within a larger UK/US group.

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.

Amazon★3.5 (56k)· London

Build machine learning and optimization models for Amazon’s Middle Mile freight marketplace using Java, C++, Python, MxNet, TensorFlow, AWS, and causal inference. The team develops forecasting, dynamic pricing, and network optimization systems to power Amazon’s external freight transportation network.

Amazon★3.5 (56k)· London

The role uses Python, Java, C++, machine learning (random forests, gradient boosting, LASSO, logistic regression) and optimization (integer programming, dynamic programming, stochastic optimization). The team builds algorithms for Amazon's freight marketplace to optimize dynamic pricing and network planning for external shippers and carriers.