1 to 25 of 98 Machine Learning Jobs in Yorkshire

products through advanced machine learning models improving search relevance, personalisation, and conversion outcomes at scale. You'll lead a talented team of ML Scientists and collaborate cross-functionally with product, data, and engineering leaders to define and execute the ML roadmap for search. This is an opportunity … Learning, Marketplace, Ecommerce, | 35 Million Users | London, Hybrid, 1 Day PW, Up to £140,000 Lead, coach, and develop a team of ML Scientists, fostering a culture of experimentation, collaboration, and continuous learning. Partner with Product, Data, and Engineering leaders to shape and deliver an actionable ML strategy ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Lead the design and analysis of A/B tests and offline … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton ...

seeking an experienced Machine Learning Engineer to support a Financial Services organisation on an initial 6-month contract, working on production-grade ML systems that operate in regulated, high-volume environments. This role is ideal for someone comfortable taking models from research through to deployment, with a strong … into production within a Financial Services environment Collaborate closely with Data Scientists, Software Engineers, Risk, and Product teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support ...

seeking an experienced Machine Learning Engineer to support a Financial Services organisation on an initial 6-month contract, working on production-grade ML systems that operate in regulated, high-volume environments. This role is ideal for someone comfortable taking models from research through to deployment, with a strong … into production within a Financial Services environment Collaborate closely with Data Scientists, Software Engineers, Risk, and Product teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support ...

seeking an experienced Machine Learning Engineer to support a Financial Services organisation on an initial 6-month contract, working on production-grade ML systems that operate in regulated, high-volume environments. This role is ideal for someone comfortable taking models from research through to deployment, with a strong … into production within a Financial Services environment Collaborate closely with Data Scientists, Software Engineers, Risk, and Product teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support ...

seeking an experienced Machine Learning Engineer to support a Financial Services organisation on an initial 6-month contract, working on production-grade ML systems that operate in regulated, high-volume environments. This role is ideal for someone comfortable taking models from research through to deployment, with a strong … into production within a Financial Services environment Collaborate closely with Data Scientists, Software Engineers, Risk, and Product teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support ...

with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, youll be working with some … models for fraud detection, credit risk, customer segmentation, and behavioural analytics using scalable frameworks like TensorFlow, PyTorch, and XGBoost. Engineer robust data pipelines and ML workflows using Apache Spark, Vertex AI, and CI/CD tooling to ensure seamless model delivery and monitoring. Apply advanced techniques in deep learning ...

problems with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineerdesigning and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, youll be working with some … models for fraud detection, credit risk, customer segmentation, and behavioural analytics using scalable frameworks like TensorFlow, PyTorch, and XGBoost. Engineer robust data pipelines and ML workflows using Apache Spark, Vertex AI, and CI/CD tooling to ensure seamless model delivery and monitoring. Apply advanced techniques in deep learning ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

Permanent Remuneration (UK – Remote): £81–108k Base Salary + Discretionary Bonus + Equity We are a stealth-mode AI laboratory researching and developing Machine Learning models. The founding team consists of Cambridge graduates and former engineers at Google, Meta, Bloomberg, Microsoft and Amazon. We are backed by prominent … institutional VC funds and C-level executives of global technology companies. The role involves the design and development of backend services and infrastructure for Machine Learning workloads. You will be working closely with the Machine Learning team; however, you are not required or expected to have ...

Permanent Remuneration (UK – Remote): £81–108k Base Salary + Discretionary Bonus + Equity We are a stealth-mode AI laboratory researching and developing Machine Learning models. The founding team consists of Cambridge graduates and former engineers at Google, Meta, Bloomberg, Microsoft and Amazon. We are backed by prominent … institutional VC funds and C-level executives of global technology companies. The role involves the design and development of backend services and infrastructure for Machine Learning workloads. You will be working closely with the Machine Learning team; however, you are not required or expected to have ...

Permanent Remuneration (UK – Remote): £81–108k Base Salary + Discretionary Bonus + Equity We are a stealth-mode AI laboratory researching and developing Machine Learning models. The founding team consists of Cambridge graduates and former engineers at Google, Meta, Bloomberg, Microsoft and Amazon. We are backed by prominent … institutional VC funds and C-level executives of global technology companies. The role involves the design and development of backend services and infrastructure for Machine Learning workloads. You will be working closely with the Machine Learning team; however, you are not required or expected to have ...

Permanent Remuneration (UK – Remote): £81–108k Base Salary + Discretionary Bonus + Equity We are a stealth-mode AI laboratory researching and developing Machine Learning models. The founding team consists of Cambridge graduates and former engineers at Google, Meta, Bloomberg, Microsoft and Amazon. We are backed by prominent … institutional VC funds and C-level executives of global technology companies. The role involves the design and development of backend services and infrastructure for Machine Learning workloads. You will be working closely with the Machine Learning team; however, you are not required or expected to have ...

/ML Engineer (Generative AI/LLMs) Location: Fully Remote (UK-based) The Role We're hiring a Senior Machine Learning Engineer to lead the design and production of Generative AI and Large Language Model (LLM) applications. This role sits at the heart of an AI-focused engineering … semi-autonomous agents using modern agent frameworks and Google AI tooling. Collaborate with product and engineering teams to translate complex business requirements into ML-driven solutions. Monitor, optimise, and continuously improve models in live production environments. Contribute to the architecture and evolution of the AI platform and supporting data infrastructure. ...

limit and you'll help us get there. Key Responsibilities Stay up to date with the state-of-the-art in Artificial Intelligence and Machine Learning, and apply it to the problem of Enterprise Vibe Coding; Make use of techniques such as In-Context Learning (Prompt Engineering … practice in a large-scale project. Qualifications/What You Need To Succeed Ph.D. or MSc degree in Computer Science, Electrical Engineering, Artificial Intelligence, Machine Learning, or related technical fields is highly valued. 7+ years of work experience in Machine Learning and AI Engineering roles, preferably ...

limit and you'll help us get there. Key Responsibilities Stay up to date with the state-of-the-art in Artificial Intelligence and Machine Learning, and apply it to the problem of Enterprise Vibe Coding; Make use of techniques such as In-Context Learning (Prompt Engineering … practice in a large-scale project. Qualifications/What You Need To Succeed Ph.D. or MSc degree in Computer Science, Electrical Engineering, Artificial Intelligence, Machine Learning, or related technical fields is highly valued. 7+ years of work experience in Machine Learning and AI Engineering roles, preferably ...

limit and you'll help us get there. Key Responsibilities Stay up to date with the state-of-the-art in Artificial Intelligence and Machine Learning, and apply it to the problem of Enterprise Vibe Coding; Make use of techniques such as In-Context Learning (Prompt Engineering … practice in a large-scale project. Qualifications/What You Need To Succeed Ph.D. or MSc degree in Computer Science, Electrical Engineering, Artificial Intelligence, Machine Learning, or related technical fields is highly valued. 7+ years of work experience in Machine Learning and AI Engineering roles, preferably ...