9 of 9 Permanent Reinforcement Learning Jobs in the UK excluding London

for domain-specific applications Implement 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 best practices in data engineering … GPT, LLaMA, Mistral, Claude) Strong 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 in a relevant field or equivalent … with industry knowledge and technology Why Join Us? Work on impactful AI projects with real-world applications Be part of a collaborative and forward-thinking team Access to continuous learning and development opportunities Flexible working arrangements and a supportive work culture Ready to shape the future of AI? Apply now and bring your expertise to a team that values More ❯

applications, APIs, or workflows (e.g., chatbots, copilots, automation tools) Collaborate with researchers, engineers, and product teams to iterate on AI capabilities Optimize AI behaviour and results through feedback loops, reinforcement learning, or user interaction Maintain thorough documentation of logic, design decisions, and dependencies Requirements BSc or MSc in Computer Science, AI/Machine Learning, CyberSecurity, or a … with AI/ML libraries (e.g., LangChain, OpenAI API, Hugging Face, PyTorch) Knowledge of application security principles and best practices Understanding of agent-based modeling, multi-agent systems, or reinforcement learning Experience building applications with LLMs or generative AI models Familiarity with API development, backend services, and deployment pipelines Ability to work independently and with a team in More ❯

AI research team and are looking for a Lead AI Technologist to help lead the team, researching and developing novel AI/ML technologies. You’ll lead projects spanning reinforcement learning, NLP, computer vision, and signal processing, while mentoring teams and shaping partnerships with academic and industry leaders. Responsibilities: Lead delivery of large-scale AI/ML projects … in engineering assurance and technical review Proposal writing experience Strong communication and mentoring skills Beneficial: Expertise in one or more of: AI/ML for imagery and remote sensing Reinforcement learning Natural Language Processing and Large Language Models Knowledge graphs and graph neural networks AI for RF, EW, radar, sonar, or acoustics Autonomy applications If you are interested More ❯

Senior Quant Machine Learning Engineer sought by leading investment bank based in the city of London. **Inside IR35, 4 days a week on site** The role:To lead the design and deployment of ML-driven models across our trading and investment platforms. This is a high-impact, front-office role offering direct collaboration with traders, quant researchers, and technologists … and scalable model infrastructure for production deployment Mentor junior quants and engineers; contribute to knowledge-sharing and model governance processes Stay current with cutting-edge ML research (e.g., deep learning, generative models, reinforcement learning) and assess applicability to financial markets Collaborate closely with cross-functional teams, including traders, data engineers, and software developers What We're Looking … fund, or tech firm Advanced degree (PhD or Master's) in Computer Science, Mathematics, Physics, Engineering, or related discipline Strong expertise in modern ML techniques: time-series forecasting, deep learning, ensemble methods, NLP, or RL Expert-level programming skills in Python and strong understanding of software engineering best practices Experience deploying ML models to production in real-time or More ❯

Overview The Senior Data Scientist is responsible for developing and implementing advanced data science models, machine learning algorithms, and predictive analytics solutions to drive business insights, product innovation, and operational efficiencies at IMS. This role plays a critical part in enhancing telematics, mobility, and insurance technology solutions through data-driven decision-making, statistical analysis, and AI-driven automation. The … a strategic mindset to solve complex problems using data science. This position is a vital component of the business, and is responsible for: Responsibilities Develop, train, and deploy machine learning models for risk scoring, behavioural analytics, fraud detection and extreme event detection. Optimize feature engineering, model performance, and real-time inference pipelines for large-scale datasets. Work on supervised … unsupervised, and reinforcement learning models to enhance decision-making. Leverage telematics, mobility, and insurance data to generate actionable insights and product improvements. Statistical Analysis and Data Modelling Conduct exploratory data analysis (EDA) to uncover trends, anomalies, and business opportunities. Ensure robustness and scalability of data science pipelines, minimizing bias and improving accuracy. Data Engineering and Infrastructure Collaborate with More ❯

the development of a cutting-edge agentic AI system for intelligent data discovery, extraction, and decision-making. Oversee the integration of LLMs, knowledge graphs, retrieval-augmented generation (RAG), and reinforcement learning for autonomous task execution. Champion the application of explainable and trustworthy AI principles in all solutions. Hands-on Technical Leadership Serve as a player-coach-writing code More ❯

Key Responsibilities: Lead development of machine learning systems for digital human avatar generation using inverse rendering and Unity-based visualization. Design and implement mesh and texture warping algorithms (energy-based methods, Thin Plate Splines). Develop inverse rasterization systems and facial feature extraction algorithms using PyTorch. Contribute to NeRF-based systems with GPU-optimized kernel development, screen space sampling … Maps. Design Unity and Unreal Engine plugins for real-time physics, rendering, and visualization. Develop modules for 3D reconstruction, mesh processing, and camera calibration using C++ and Python. Implement reinforcement learning systems for animation synthesis and optimization-based cloth simulation. Build OpenGL/Compute shaders and GPU kernels for performance-critical 3D applications. Requirements: Degree in Computer Science More ❯

in the field, using your knowledge of state-of-the-art techniques to solve problems. LLMs will be your bread and butter, customized with advanced RAG techniques, finetuning and reinforcement learning. You'll work closely with other engineers to build fast, and you'll use Python and Kubernetes to deploy systems in production. What you'll do Work with … LLMs understand and interact with the millions of lines of code that run Kraken, leveraging techniques at the cutting-edge of the technology like GraphRAG, agentic workflows, finetuning, and reinforcement learning Use classic ML and NLP techniques to complement and improve LLM systems Act as a center of excellence for the whole business in AI, as a floating More ❯

Excellent communication and remote collaboration skills Nice to Have Experience with Julia Knowledge of applied category theory (e.g. algebraic theories, presheaves, coalgebra, polynomial functors) Background in model-based deep reinforcement learning, program synthesis, or theorem proving Willingness to deepen theoretical knowledge as needed Why This Role? This is a unique opportunity to work on a high-impact project More ❯