5 Reinforcement Learning Jobs in the UK with Remote Work Options

fertility, pregnancy and menopause. This is a fully remote position and the salary is between 50-75k. They are looking for a Machine Learning engineer who can lead the company’s AI R&D to leverage cutting edge research and incorporate emerging technologies into their NLP and conversational … AI solutions Essential skills 4+ years of industry experience in developing Machine Learning models and maintaining them in a production environment Solid understanding of Machine learning concepts and algorithms, including supervised and unsupervised learning, deep learning and reinforcement learning. Experience with NLP and LLMs’ and … attention mechanism, transformer technologies etc.) Experience in deploying NLP pipelines to production Python experience including data science libraries (scikit-learn, pandas, NumPy) and deep learning frameworks (Tensorflow, Pytorch) Desirable Experience with virtual agent platforms such as IBM Watson or DialogFlow Team leading experience Proven experience in CI environments, unit more »

researchers from various disciplines. Responsibilities : Research and Development: Stay updated with the latest advancements in AI, specifically focusing on Large Language Models (LLMs) and Reinforcement Learning (RL). Develop and implement innovative solutions to improve existing systems or create new ones. Model Training and Integration : Train and integrate … machine learning models, with a particular focus on LLMs. Utilise techniques such as transfer learning and fine-tuning to adapt pre-trained models to specific tasks or domains. Engineering : Apply strong coding skills in Python to develop and maintain robust, scalable systems. Follow object-oriented design principles and … positive and collaborative team environment. MLOps and Deployment : Apply knowledge of MLOps principles and practices to streamline the development, deployment, and monitoring of machine learning systems. Deploy ML models into production environments. Requirements : Master's or PhD in Computer Science, Engineering, or a related field. 5+ years' experience with more »

highly transferable skill analogues Experience developing and evaluating models using at least one of the following technologies: —- Gradient-boosted decision trees (e.g. Catboost, XGBoost) —- Reinforcement learning —- Recommendation systems —- Large language models Able to train, tune and evaluate models and prepare them for production deployment Understanding and experience with … problems, contributes to discussion and helps refine technical requirements Delivers consistently under a typical collaborative framework (e.g. agile) Can explain complex statistical and machine learning concepts and their results in a clear way, through visualisations and data summarisation, including to non-technical audiences Through experience, research, and/or … best tools available; doesn't hack fragile things together for short-term speed or to avoid discussion Ideal/Bonus Points Insatiable thirst for learning and acquiring new knowledge, skills and experience Positive force in building up the team as we grow and develop into more senior positions Introduces more »

product and engineering teams across the globe. The Intelligent Systems team is at the forefront of driving innovation through cutting-edge data science, machine learning, and generative AI technologies. As a crucial part of our organization, this team is poised for substantial growth in the coming year and beyond. … development life cycle. Automating quality assurance processes and cloud resource allocation in software development. Requirements PhD or advanced Masters in Statistics, Computer Science, Machine Learning & AI, Mathematics, or Physics. Hands-on experience in at least three of the following areas: Generative AI, Supervised and Unsupervised Learning, Deep Learning, Computer Vision, Recommendation Systems, Knowledge Graphs, Probabilistic Inference, Bayesian Statistics, Reinforcement Learning. Strong industry experience, with a focus on taking concepts and models from conception to production and quantifying business impact. Proficiency in Python programming. Expertise in GIT and the data science Python stack. Experience with real-world more »

product and engineering teams across the globe. The Intelligent Systems team is at the forefront of driving innovation through cutting-edge data science, machine learning, and generative AI technologies. As a crucial part of our organization, this team is poised for substantial growth in the coming year and beyond. … development life cycle. Automating quality assurance processes and cloud resource allocation in software development. Requirements PhD or advanced Masters in Statistics, Computer Science, Machine Learning & AI, Mathematics, or Physics. Hands-on experience in at least three of the following areas: Generative AI, Supervised and Unsupervised Learning, Deep Learning, Computer Vision, Recommendation Systems, Knowledge Graphs, Probabilistic Inference, Bayesian Statistics, Reinforcement Learning. Strong industry experience, with a focus on taking concepts and models from conception to production and quantifying business impact. Proficiency in Python programming. Expertise in GIT and the data science Python stack. Experience with real-world more »