26 to 33 of 33 Reinforcement Learning Jobs in the Midlands

the brief with stakeholders, data gathering, feature engineering, & model delivery right through to stakeholder model presentation. Data analysis and modelling: Utilise statistical and experimental techniques, predictive modelling, and machine learning algorithms to analyse large and complex datasets related to pricing, promotions, sales, and customer behaviour. Extract actionable insights to support pricing decision-making. Develop a price optimisation tool to … us to optimise pricing for profit or revenue growth, based on measured elasticity at either a category or SKU level. This could take several forms (Regression based, Experimental/Reinforcement Learning, Bayesian) but you’d be responsible ultimately for the success of the model. Commercial forecasting support Develop forecasting models to predict pricing trends, demand patterns, and market More ❯

Direct message the job poster from The Portfolio Group Chief Operations Officer at The Portfolio Group | Executive Recruitment & Search Assignments. An exceptional opportunity for a Machine Learning Engineer (with Full-Stack experience) to join an innovative market leader at the forefront of developing next-generation solutions that transform digital interactions. The role will focus on projects to leverage state … of-the-art generative AI, retrieval-augmented generation (RAG), and reasoning frameworks to build intelligent and context-aware systems. We are seeking talented Machine Learning Engineers with full-stack software development experience to join our client’s team and help shape the future of AI-powered automation. Within this dynamic role varied duties will include: Search relevancy engineering. Conversational … Implement, optimise, and scale RAG pipelines for effective information retrieval from structured and unstructured sources. Model Fine-Tuning & Training : Train domain-specific models using techniques like LoRA, QLoRA, PEFT, reinforcement learning, and supervised fine-tuning (SFT). Model Deployment & Inferencing : Optimise model serving and inference using vLLM, DeepSpeed, TensorRT, Triton, and other acceleration frameworks. Multi-Agent Systems : Develop More ❯

An exceptional opportunity for a Machine Learning Engineer (with Full-Stack experience) to join an innovative market leader at the forefront of developing next-generation solutions that transform digital interactions. The role will focus on projects to leverage state-of-the-art generative AI, retrieval-augmented generation (RAG), and reasoning frameworks to build intelligent and context-aware systems. We … are seeking talented Machine Learning Engineers with full-stack software development experience to join our client's team and help shape the future of AI-powered automation. Within this dynamic role varied duties will include: Search relevancy engineering. Conversational AI Development : Design, train, fine-tune, and deploy LLMs with reasoning capabilities. Retrieval-Augmented Generation (RAG): Implement, optimise, and scale … RAG pipelines for effective information retrieval from structured and unstructured sources. Model Fine-Tuning & Training : Train domain-specific models using techniques like LoRA, QLoRA, PEFT, reinforcement learning, and supervised fine-tuning (SFT). Model Deployment & Inferencing : Optimise model serving and inference using vLLM, DeepSpeed, TensorRT, Triton, and other acceleration frameworks. Multi-Agent Systems : Develop and integrate agentic capabilities More ❯

An exceptional opportunity for a Machine Learning Engineer (with Full-Stack experience) to join an innovative market leader at the forefront of developing next-generation solutions that transform digital interactions. The role will focus on projects to leverage state-of-the-art generative AI, retrieval-augmented generation (RAG), and reasoning frameworks to build intelligent and context-aware systems. We … are seeking talented Machine Learning Engineers with full-stack software development experience to join our client's team and help shape the future of AI-powered automation. Within this dynamic role varied duties will include: Search relevancy engineering. Conversational AI Development : Design, train, fine-tune, and deploy LLMs with reasoning capabilities. Retrieval-Augmented Generation (RAG): Implement, optimise, and scale … RAG pipelines for effective information retrieval from structured and unstructured sources. Model Fine-Tuning & Training : Train domain-specific models using techniques like LoRA, QLoRA, PEFT, reinforcement learning, and supervised fine-tuning (SFT). Model Deployment & Inferencing : Optimise model serving and inference using vLLM, DeepSpeed, TensorRT, Triton, and other acceleration frameworks. Multi-Agent Systems : Develop and integrate agentic capabilities More ❯

be part of The Online 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 colleagues in the wider Online … We are looking for a technically strong and strategically minded Senior AI/ML 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 and deliver a programme of work … that will develop and share fundamental understanding of the Artificial Intelligence and Machine Learning technologies that underpin online services to help meet Ofcom's Online Safety objectives. This position is ideal for candidates with deep technical expertise and a passion for applying AI responsibly in complex socio-technical environments. Your Key Responsibilities Technical Advisory & Policy Support Provide expert guidance More ❯

. Leadership - you’ve run small technical teams, worked directly with product, clients, and stakeholders. A solid background in AI (Engineering rather than Research) Possess a deep understanding of reinforcement learning, distributed training and Agentic AI Not for you if: You’re more strategist than builder. Your AI experience is just post-ChatGPT. You’re mainly delivering analytics More ❯

. Leadership - you’ve run small technical teams, worked directly with product, clients, and stakeholders. A solid background in AI (Engineering rather than Research) Possess a deep understanding of reinforcement learning, distributed training and Agentic AI Not for you if: You’re more strategist than builder. Your AI experience is just post-ChatGPT. You’re mainly delivering analytics More ❯

. Leadership - you’ve run small technical teams, worked directly with product, clients, and stakeholders. A solid background in AI (Engineering rather than Research) Possess a deep understanding of reinforcement learning, distributed training and Agentic AI Not for you if: You’re more strategist than builder. Your AI experience is just post-ChatGPT. You’re mainly delivering analytics More ❯