21 of 21 Reinforcement Learning Jobs in London

Responsibilities Actively contribute to the design, development, testing, and evaluation of data science solutions Train and deploy state-of-the-art machine learning and reinforcement learning models Build AI systems using Large Language Models Build processes for extracting, cleaning and transforming data (SQL/Python … stakeholders Experience of proactively contributing to the design, development, testing, and deployment of data science and AI solutions Experience and understanding of applied machine learning techniques in Python (e.g. xgboost, regression, decision trees) Experience with physics modelling highly desirable Practical knowledge and experience of developing AI solutions using advanced ...

Responsibilities Actively contribute to the design, development, testing, and evaluation of data science solutions Train and deploy state-of-the-art machine learning and reinforcement learning models Build AI systems using Large Language Models Build processes for extracting, cleaning and transforming data (SQL/Python … stakeholders Experience of proactively contributing to the design, development, testing, and deployment of data science and AI solutions Experience and understanding of applied machine learning techniques in Python (e.g. xgboost, regression, decision trees) Experience with physics modelling highly desirable Practical knowledge and experience of developing AI solutions using advanced ...

Machine Learning Engineer/ML Engineer Machine Learning Development Design and implement machine learning models for financial applications, with a focus on pricing and risk analytics Build scalable ML pipelines for processing large-scale financial data Develop deep learning architectures for time series prediction, anomaly detection … data-driven approaches to complement traditional quantitative finance models Support implementation of ML solutions for derivatives pricing and risk management Core Technical Skills Machine Learning Expertise : Deep understanding of ML algorithms (supervised/unsupervised learning, reinforcement learning) Extensive experience with neural networks, including RNNs, LSTMs, Transformers ...

improving architecture and developing reusable data pipelines, APIs, and components Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms Contribute to shaping Braze's product strategy and roadmap through customer-facing insights and technical expertise Provide ongoing technical … required; Master’s or PhD in a relevant technical discipline preferred Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred Strong technical ...

these AI solutions to ensure they meet user needs and drive meaningful impact in both healthcare and accessibility domains. Responsibilities: Develop and optimize machine learning models for disease prediction, early diagnosis and personalised healthcare solutions. Process and analyze structured and unstructured health data (EHR, Wearables, HL7/FHIR … implement deep learning algorithms for predictive healthcare applications. Contribute to research on AI-driven personalization strategies to empower users in managing their health effectively. Develop AI-powered accessibility solutions for our products, leveraging multi-modal AI (text, image, audio). Adhere to data privacy regulations (GDPR, MDR, HIPPA, EHDS ...

these AI solutions to ensure they meet user needs and drive meaningful impact in both healthcare and accessibility domains. Responsibilities: Develop and optimize machine learning models for disease prediction, early diagnosis and personalised healthcare solutions. Process and analyze structured and unstructured health data (EHR, Wearables, HL7/FHIR … implement deep learning algorithms for predictive healthcare applications. Contribute to research on AI-driven personalization strategies to empower users in managing their health effectively. Develop AI-powered accessibility solutions for our products, leveraging multi-modal AI (text, image, audio). Adhere to data privacy regulations (GDPR, MDR, HIPPA, EHDS ...

these AI solutions to ensure they meet user needs and drive meaningful impact in both healthcare and accessibility domains. Responsibilities: Develop and optimize machine learning models for disease prediction, early diagnosis and personalised healthcare solutions. Process and analyze structured and unstructured health data (EHR, Wearables, HL7/FHIR … implement deep learning algorithms for predictive healthcare applications. Contribute to research on AI-driven personalization strategies to empower users in managing their health effectively. Develop AI-powered accessibility solutions for our products, leveraging multi-modal AI (text, image, audio). Adhere to data privacy regulations (GDPR, MDR, HIPPA, EHDS ...

interactive workshop to teach artificial intelligence concepts through guided exercises and discussion Serve as a thought leader, evangelizing the benefits of AI testing & reinforcement learning Maintain deep understanding of competitive and complementary technologies and vendors and how to position Braze in relation to them Collaborate cross-functionally (e.g. … presenter: You are an enthusiastic and engaging presenter, with the ability to communicate effectively with a wide range of stakeholders An expert in machine learning: You have a solid grasp of machine learning, including a familiarity with reinforcement learning Mar-tech savvy: You understand the marketing ...

currently working on an AI Engineer role with a global language and translation company. You will be designing, developing, and deploying cutting-edge machine learning solutions across the company.If you enjoy end-to-end ownership (from experimentation to deployment), working with AWS, Docker, MLflow, TensorFlow/PyTorch, and contributing … code in Python Experience with TensorFlow, PyTorch and Scikit-learn Experience with NLPs and LLMs Speech, Text or Audio data Strong knowledge of machine learning techniques and algorithms, including supervised and unsupervised learning, deep learning, and reinforcement learning ...

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 … 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 ...

Machine Learning Engineer (LLM/AI Systems) London/Hybrid | 0–3 Years Experience | Competitive Salary Are you obsessed with AI and large language models? We’re an early-stage startup building real-world products powered by LLMs — from intelligent copilots to adaptive automation tools — and we’re looking … research — we give you time and resources to explore, learn, and publish. What We’re Looking For 0–3 years of experience in Machine Learning, Data Science, or NLP/LLM. Strong Python skills; exposure to PyTorch/TensorFlow/Hugging Face. (Bonus) understand fundamentals of deep learning ...

Senior Machine Learning Engineer (Generative AI/LLMs) Location: Fully Remote (UK-based) Salary: £75,000 - £100,000 (depending on experience) The Role We're hiring a Senior Machine Learning Engineer to lead the design and productionisation of Generative AI and Large Language Model (LLM) applications. This role … strong influence over architecture, tooling, and the future direction of LLM-powered products. What You'll Be Doing Design, develop, and deploy advanced machine learning and deep learning models into production. Architect scalable LLMOps pipelines on GCP/Vertex AI , including fine-tuning, vector search, and low-latency ...

user behaviour with respect to ads quality* Building a solid infrastructure around signals, labels and quality metricsWe work at the intersection of Ads, Machine Learning and User Behaviour understanding. The nature of our work is very analytical, with a solid collaboration with our Data Scientist and a heavy focus … roadmap for large cross-company efforts Suggest, collect and synthesize requirements and create an effective feature and technology roadmap Minimum Qualifications: Experience developing machine learning algorithms or machine learning infrastructure in Python, PyTorch, and/or C/C++ Bachelor in Artificial Intelligence (AI), computer science, related technical ...

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 … 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 ...

languages. 3 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field. 3 years of experience with ML infrastructure (e.g., model deployment … Python. Experience with an emphasis on algorithms, systems and tools for ML performance projections and evaluation. Experience designing or implementing components of a Deep Learning Compiler Stack (e.g., XLA, MLIR, TVM, ONNX Runtime). Experience in low-latency systems programming (e.g., C/C++) and optimizing data movement across ...

C++. Excellent collaboration and communication skills. Ability to commit 20–30 hours per week. Preferred Familiarity with LLM inference pipelines, multi-agent architectures, or reinforcement learning environments. Knowledge of network optimization, data streaming, and caching architectures. Application Process (Takes 20–30 mins to complete) Upload resume AI interview ...

Safety Technology team conducts research to build knowledge and understanding in subject areas fundamental to online safety. This includes, for example, AI and machine learning, digital identity, privacy enhancing technologies, decentralisation, user experience, gaming, network infrastructure, and digital forensics. The team provides technical expertise to policy, supervision and enforcement … technically strong and strategically minded AI/ML Senior Technology Advisor to provide expert guidance on the technical aspects of artificial intelligence and machine learning as they relate to online safety. The successful candidate will play a leading role within the Online Safety Technology team to help design ...

Models (LLMs) and other generative architectures. Optimise pre-trained models (OpenAI, Anthropic, or open-source LLMs) for business use cases using prompt engineering and reinforcement learning. Experiment with model configurations to balance performance, cost, and scalability. Build robust data pipelines for continuous model improvement and retraining. Ensure compliance with ...

Models (LLMs) and other generative architectures. Optimise pre-trained models (OpenAI, Anthropic, or open-source LLMs) for business use cases using prompt engineering and reinforcement learning. Experiment with model configurations to balance performance, cost, and scalability. Build robust data pipelines for continuous model improvement and retraining. Ensure compliance with ...

final polish to ensure the AI sounds human and helpful. Rate and rank multiple model outputs to provide the "ground truth" data needed for Reinforcement Learning (RLHF). Qualifications: Proven experience in content moderation, editing, or quality assurance (QA). Sharp analytical skills with the ability to detect ...

improve multimodal LLMs to achieve new functionality for our customers and optimize their deployments (cloud and edge). Some of our deep learning models are truly tiny - the memory footprint of our smallest computer vision model is just 1MB. You will train and design more accurate models, while also … LLMs. Trained neural networks that moved into production. Nice To Have Industry experience with efficient inference deployments (cloud or edge). Experience with Deep Reinforcement Learning. What we offer Competitive salary. Generous equity stake in the company. Relocation assistance. Choose your own laptop. 25 days of paid vacation time ...