10 of 10 Remote/Hybrid Reinforcement Learning Jobs in England

permanent position with candidates required to do hybrid working in either Cambridge or London. Our client are looking for AI Researchers specialising in Reinforcement Learning with Human Feedback (RLHF) and Generative AI. In this role, you will design and optimise the algorithms that align large-scale generative models … build the next generation of foundation models Responsibilities: Develop and refine RLHF algorithms for large language and generative models. Research and implement deep reinforcement learning methods (policy gradients, actor-critic, off-policy learning) for model alignment. Train, fine-tune, and evaluate LLMs and diffusion models at scale. ...

faster and that genuinely meet user needs at national scale. Youll play a key role in exploring complex datasets, building production-ready machine learning and generative AI solutions, and working closely with multidisciplinary teams to translate real user problems into impactful AI capabilities. Key responsibilities include: Exploring, analysing … interpreting large, complex and diverse datasets to uncover insights and opportunities for AI-driven improvement. Designing, building, evaluating and optimising machine learning, deep learning and generative AI models for real-world service applications. Collaborating with engineers, product managers, designers and policy stakeholders to translate user needs into scalable ...

Hybrid): 2 days from office Number of Positions: 4 The Role An AI/ML Developer is responsible for designing, building, and deploying machine learning models and AI solutions that solve business problems. This role focuses on coding, data preparation, and integrating models into production systems. Your Responsibilities … Model Development Design, build, and train machine learning models for predictive analytics, classification, NLP, computer vision, or other AI applications. Experiment with algorithms and optimize hyperparameters for performance. Data Preparation Collect, clean, and preprocess large datasets for training and validation. Implement feature engineering and data augmentation techniques. Integration & Deployment ...

Responsibilities End-to-End Delivery: Lead the technical execution of AI projects, from initial problem discovery and hypothesis testing to deploying production-grade machine learning models. Strategic Advisory: Act as a "translator" between technical complexity and business value. You will work closely with C-suite stakeholders to identify … solve their most pressing strategic challenges. Technical Leadership: Architect robust, scalable data pipelines and state-of-the-art models (including LLMs, Reinforcement Learning, or Bayesian Inference) tailored to specific client needs. Mentorship: Guide and upskill junior Data Scientists, fostering a culture of rigorous peer review, clean coding standards ...

Machine Learning Engineer (PyTorch LLM) London onsite to £110k Do you have expertise with Machine Learning in production? You could be progressing your career at a London based tech start-up with £5 million in recent pre-seed funding, in an impactful role that you'll shape. … product is an AI agentic based platform that writes production grade code. As a Machine Learning Engineer you'll take open-source LLMs (code and general models) and turn them into high-performance software engineer agents using supervised fine tuning and large scale reinforcement learning. This ...

L3RPEY-EE99B2CA) London, EnglandSalary: GBP70000 - GBP100000 per annumLead Data Scientist - Adtech BusinessI am recruiting for a Lead Data Scientist to drive innovation in machine learning and data-driven solutions, particularly within AdTech. This fully remote role is ideal for someone passionate about optimising algorithms, building scalable models, and solving … complex business challenges for clients & customers.Key Responsibilities:Develop and deploy machine learning models to enhance advertising performance.Optimise real-time decision-making algorithms in programmatic advertising.Work with data engineers to build scalable, production-ready data pipelines.Apply advanced ML techniques like reinforcement learning and deep learning.Collaborate with cross-functional ...

Responsibilities Modelling and Forecasting Develop time‐series models for generation, consumption, and market price forecasting. Build probabilistic and scenario‐based forecasting capabilities. Apply machine learning to optimise matching, pairing, and routing algorithms within the P2P marketplace. Trading and Optimisation Intelligence Create algorithms that optimise buyer–seller matching, pricing … learn, PyTorch/TensorFlow). Strong experience with time‐series modelling (ARIMA, Prophet, LSTMs or similar). Understanding of optimisation methods (linear, mixed‐integer, reinforcement learning desirable). Strong SQL and practical experience with production‐ready data pipelines. Experience working with cloud environments (AWS, GCP, or Azure). ...

large-scale open-source projects. You will also have the opportunity to teach on the fellowship about topics that range from basic statistics to reinforcement learning, and to mentor the fellows through their 6-week project.Thanks to Faculty platform, you will have access to powerful computational resources … programmer in a short timeframeAn excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe)A high level of mathematical competence and proficiency in statisticsA solid grasp of essentially all of the standard data ...

path toward deployment and commercial relevance. Initial focus areas include: Agentic AI systems Energy systems flexibility Creative industries applications Emerging work across generative AI, reinforcement learning, neuro-symbolic AI, verifiable AI, and MCP-style architectures You will work closely with academic partners, industry collaborators, and funding bodies, translating ...

vector search technology. Collaborate with cross-functional teams to integrate AI models into products. Stay updated with the latest advancements in AI and machine learning technologies. Conduct research to improve existing AI systems and develop new approaches. Knowledge of NLP, computer vision, or reinforcement learning. Experience deploying … models in production environments. Your Profile Essential Skills/Knowledge/Experience Proven experience in AI, machine learning, or deep learning. Proficiency in programming languages such as Python, R, or Java. Experience with AI frameworks like TensorFlow, PyTorch, or Keras. Experience with large language models (GPT, BERT, etc.). ...