4 of 4 Remote Reinforcement Learning Jobs in London

ownership. As we scale, opportunities to 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 and systems-level engineering within the same afternoon. Required Qualifications Education & Experience: PhD in … physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and data structures. More ❯

ownership. As we scale, opportunities to 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 and systems-level engineering within the same afternoon. Required Qualifications Education & Experience: PhD in … physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and data structures. More ❯

of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: You want to build and run elegant and thorough machine learning experiments to help us understand and steer the behavior of powerful AI systems. You care about making AI helpful, honest, and harmless, and are interested in the ways that … Testing the robustness of our safety techniques by training language models to subvert our safety techniques, and seeing how effective they are at subverting our interventions. Run multi-agent reinforcement learning experiments to test out techniques like AI Debate. Build tooling to efficiently evaluate the effectiveness of novel LLM-generated jailbreaks. Write scripts and prompts to efficiently produce … efforts Pick up slack, even if it goes outside your job description Care about the impacts of AI Strong candidates may also: Have experience authoring research papers in machine learning, NLP, or AI safety Have experience with LLMs Have experience with reinforcement learning Have experience with Kubernetes clusters and complex shared codebases Candidates need not have More ❯

Role - Machine Learning Engineer Location Hybrid, 1 day on site in London (with flex) Salary - £70,000 to £75,000 The Opportunity Were partnering with a client in the financial services sector who are looking to bring on a Machine Learning Engineer to their growing Intelligent Automation Team of 50. Following a period of significant transformation and with … a strong benefits package. The position is hybrid, typically one day per week on site in London (with flexibility around which day). The Role Reporting to the Machine Learning Lead, youll be a hands-on Machine Learning Engineer with a strong track record of building and deploying ML solutions at scaleparticularly in NLP and GenAI. You will … ARM, Terraform). A test-driven development mindset and commitment to engineering quality. Broad understanding of ML approaches, with the ability to explain methods clearly: Regression, clustering, decision trees, reinforcement learning Gradient boosting, CNNs, RNNs, LSTMs Attention models, encoder/decoder architectures, transformers, vector semantics Demonstrable experience developing GenAI applications in real-world settings. The confidence to communicate More ❯