1 to 25 of 74 Permanent Reinforcement Learning Jobs in the UK excluding London

advanced prompt engineering strategies Leverage Retrieval-Augmented Generation (RAG) for enhanced contextual performance Build intelligent agents using frameworks like LangChain, LlamaIndex, CrewAI, AutoGen Apply reinforcement learning techniques including Q-learning , policy gradients , and RLlib Collaborate with cross-functional teams to integrate AI solutions into scalable products Ensure … background in fine-tuning and prompt engineering Hands-on experience with RAG pipelines Familiarity with Agent Frameworks (LangChain, LlamaIndex, CrewAI, AutoGen) Solid understanding of reinforcement learning concepts and tools (Q-learning, policy gradients, RLlib) Azure AI Engineer Associate certification (or willingness to obtain) Bachelor's degree

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory

build and lead teams. We're hiring immediately. What You'll Actually Do Derive mathematical formulations of abstract concepts. Design and implement novel learning approaches informed by physics and mathematics. Take concepts from statistical mechanics, information theory, and dynamic systems to construct first principles algorithms. Optimise using advanced mathematical … structures, such as tensor networks, and techniques like reinforcement learning - make these approaches work in a production system. Debug why your theoretically sound approach breaks at scale. Fix it. Ship it. Daily reality includes mathematical derivations and performance optimisation. You'll need to be comfortable moving between theory