9 of 9 Reinforcement Learning Jobs in London

high-impact data science initiatives end-to-end, including problem framing, methodology selection, experiment development, implementation partnership, and impact measurement.* Build and deliver machine learning and reinforcement learning solutions to improve player engagement, retention, monetization, and operational outcomes.* Lead the modeling framework for complex systems, guaranteeing comprehensive … evaluation and monitoring of causal inference, uplift modeling, sequential decisioning, bandits/reinforcement learning, and forecasting.* Partner with game teams to define success metrics, guardrails, and decision frameworks, translating analytical results into actionable product and operational actions.* Define and uphold engineering standards and guidelines for model development, including ...

team building AI-driven trading and quantitative systems operating at significant scale across global financial markets. You will work at the intersection of machine learning, time-series modelling, and algorithmic strategy developing models that directly influence trading decisions and market performance. If you have a strong background … latency ML solutions, and play a key role in defining the technical architecture of the platform. Requirements Master's or PhD in Machine Learning, AI, CompSci, Mathematics, or a quantitative discipline 5+ years of ML engineering experience, ideally within finance or a quantitative environment Expert in Python and deep ...

work in small, collaborative teams to explore ideas, test solutions, and scale products that deliver meaningful value to customers. Our environment supports autonomy, learning, and inclusive collaboration.**About the Role**As a **Senior Principal Data Scientist**, you will contribute deep technical expertise while helping shape best practices across … apply advanced analytics to real‐world problems.### **Responsibilities:*** **Technical Leadership** Act as the go-to expert for **state-of-the-art** advanced analytics, machine learning, and generative AI. Define and evolve best practices for complex modeling and design problems, ensuring scalability, robustness, and performance. Provide thought leadership on emerging ...

preprocessing to ensure high-quality inputs for ML models. Model Development: Select and train appropriate architectures (BERT, GPT, etc.) using supervised, unsupervised, or reinforcement learning strategies. Prompt Engineering: Design, test, and iterate on complex prompts to elicit high-quality responses from LLMs while mitigating unintended behaviors. Evaluation & Optimization … establish automated monitoring systems to track drift and performance. Technical Requirements Core AI/ML: Strong experience in ML algorithms, LLM architectures, and deep learning frameworks. Generative AI: Proven expertise in Prompt Engineering and fine-tuning pre-trained models. Engineering: Proficiency in Python and experience designing data pipelines ...

maximise crop yields and minimise resource consumption, working closely with our agronomy experts. Technical skills Strong background in at least one of Machine Learning, Optimisation, Control (Model Predictive Control, Optimal Control, and classical feedback techniques), Reinforcement Learning, Physics Modelling and Numerical Simulation. Experience training Machine Learning ...

technology to let us do this. About the team: Our data science team (currently six data scientists) work across the business to deploy machine learning approaches that are helping us realise our ambition of becoming the global leader in packaged holidays. The team focuses on building value … customers, suppliers and loveholidays through deployment of advanced machine learning techniques. The impact you’ll have: Reporting directly to the VP of Data, you will lead the function that embeds intelligence at the heart of how we grow. You will define and drive Data Science’s contribution to core ...

role: Design, build, and maintain AI models and agentic systems that improve regulatory services and internal operations. Develop and tune machine learning models to ensure accuracy, fairness, and reliability in production use. Orchestrate intelligent automation workflows using low code/no code platforms and agentic AI frameworks. Monitor … secure handling of sensitive data, and regulatory considerations. Knowledge of MLOps/DevOps practices, including CI/CD pipelines for ML models. Understanding of reinforcement learning, multi-agent systems, or advanced optimization methods. Previous experience working in regulated industries is advantageous. In the first instance, please submit your ...

role: Design, build, and maintain AI models and agentic systems that improve regulatory services and internal operations. Develop and tune machine learning models to ensure accuracy, fairness, and reliability in production use. Orchestrate intelligent automation workflows using low code/no code platforms and agentic AI frameworks. Monitor … secure handling of sensitive data, and regulatory considerations. Knowledge of MLOps/DevOps practices, including CI/CD pipelines for ML models. Understanding of reinforcement learning, multi-agent systems, or advanced optimization methods. Previous experience working in regulated industries is advantageous. In the first instance, please submit your ...

Clear communication with technical and non-technical users. Strong intuition for physical and biological systems. Strong foundations in at least one of Machine Learning, Optimisation, Control (Model Predictive Control, Optimal Control, and classical feedback techniques), Reinforcement Learning, Physics Modelling and Numerical Simulation. Experience building useful tools quickly ...