1 to 25 of 36 Machine Learning Jobs in West London

fantastic opportunity for a Senior Machine Learning Scientist to work for a health-tech software company developing advanced machine learning models used within clinical research. The organisation applies modern machine learning techniques to complex medical datasets to support better understanding of patient outcomes … Scientist/Machine Learning Researcher/AI Research Scientist/Computer Vision Scientist/Deep Learning Scientist/AI Scientist/ML Research Engineer/Python/PyTorch/Deep Learning/Computer Vision/3D Imaging/Volumetric Imaging/Self-Supervised Learning/ ...

advanced machine learning and computer vision models used within clinical research and drug development. The business is building large-scale, production-grade ML systems applied to complex 3D imaging data. This role is highly engineering-focused, sitting between machine learning, infrastructure and deployment. You will work … closely with ML Scientists and engineering teams to ensure models can be trained and deployed reliably at scale. Location: 1 day per week in London - Shepherd's Bush (4 days remote) Salary: £70,000 £90,000 per annum, with flexibility for the right candidate, plus benefits Requirements for Senior/ ...

Description:- We are seeking a highly skilled Data Scientist AI to design, develop, and deploy advanced machine learning and artificial intelligence solutions. The ideal candidate will work on large datasets, build predictive models, and collaborate cross-functionally … deliver scalable, data-driven products. Key Responsibilities:- Design, develop, and optimize machine learning and deep learning models. Work on AI/ML projects including NLP, computer vision, recommendation systems, and generative AI. Perform data cleaning, feature engineering, and exploratory data analysis (EDA). Build and manage data ...

Europe once in a month (European country) We are seeking a highly skilled 12+ years Data Scientist AI to design, develop, and deploy advanced machine learning and artificial intelligence solutions. The ideal candidate will work on large datasets, build predictive models, and collaborate cross-functionally … deliver scalable, data-driven products. Key Responsibilities Design, develop, and optimize machine learning and deep learning models. Work on AI/ML projects including NLP, computer vision, recommendation systems, and generative AI. Perform data cleaning, feature engineering, and exploratory data analysis (EDA). Build and manage data ...

pipelines to support feature engineering and model training across large structured and unstructured datasets, leveraging cloud‐native tooling. Production Deployment: Deploy, monitor, and maintain ML models in production environments, including cloud‐based model serving on GCP. Ensure high availability, strong performance, and continuous model relevance. Experimentation: Lead A/… offline experimentation to evaluate model performance and guide ongoing improvement. Cross‐Functional Collaboration: Work closely with engineering, product, data, and research teams to ensure ML solutions align with product and business goals. Research & Innovation: Stay informed on advances in machine learning, deep learning, and personalisation, and evaluate ...

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 ...

leading technology consultancy is seeking an experienced Machine Learning Operations Engineer to help deploy AI/ML solutions into production environments across a range of client engagements. This role is focused on operationalising models (MLOps/AIOps), rather than building ML applications from scratch. Key Responsibilities Design … develop machine learning operational processes across diverse client environments Analyse client requirements and provide clear technical recommendations Manage the full ML lifecycle, including data selection, model deployment, operationalisation, and monitoring Develop Infrastructure as Code for ML platforms using AWS CDK Collaborate closely with data scientists to productionise ML ...

Data Scientist is accountable for the full value chain of building industrialised data-science software products, including: Business problem understanding Analysis and visualisation Prototyping ML and optimisation models in Python Production-grade software development Data pipelines and orchestration CI/CD, testing, logging, and robustness Stakeholder engagement and roadmap contribution … proactive, resilient Data-driven and pragmatic Collaborative technologist Skills and Capabilities Machine learning, optimisation, and operations research Fluent Python; strong DS/ML libraries Cloud platforms (AWS preferred) CI/CD, orchestration, containerisation Strong SQL and data engineering skills Excellent communication and analytical ability Qualifications and Experience Strong ...

satisfaction from day one. Experience in building reusable AI components and frameworks for enterprise-scale deployments.Your CV must evidence strong proficiency in Python and ML frameworks (TensorFlow, PyTorch). You will have strong statistical and analytical skills. You will be experienced in a wide range of Data Science techniques (e.g. … ML, Optimisation, Simulation, GenAI, etc.). You will have demonstrated an ability to take models from design through to production deployment, including performance optimisation, monitoring, and integration into business workflows beyond proof-of-concept or prototype stages. You will have significant experience in similar operational research roles, with a proven ...

build, testing, and deployment into production, ensuring solutions deliver tangible business value. The ideal candidate will bring deep technical expertise in AI and machine learning, coupled with strong solution architecture skills and the ability to engage confidently with business stakeholders. Experience with automation (Automation Anywhere, Microsoft Power Platform … successful candidate will hold a bachelor's degree in Computer Science, Engineering, or a related field, with significant hands-on experience in AI, machine learning, or data science projects. Strong programming skills such as Python, Java, C#, or JavaScript are required, along with experience in solution architecture, cloud ...

Replit, Bolt APIs & Microservices: RESTful APIs, GraphQL, microservice architectures Cloud & DevOps: AWS, Azure, or GCP; Docker; CI/CD pipelines Data Integration: Products integrating ML/AI models, databases, BI tools UI/UX Awareness: Collaborate on interfaces, data visualisation, user journeys Other: Version control (Git/GitHub), testing frameworks … facing products Proven experience in rapid prototyping, innovation labs, or product R&D teams Commercial experience with AI enabled products using GenAI (LLMs) or Machine Learning Familiarity with compliance, retail, FMCG, or operational intelligence systems (advantageous) Prior startup or SME experience where engineers own end-to-end delivery ...

communicate model selection, deployment strategies and the rationale behind technical decisions, fostering transparency and trust. Mentor and develop team members, promoting innovation, continuous learning, and professional growth within the London Data Science team. Maintain rigorous quality assurance and governance protocols for all AI projects, ensuring compliance with ethical … translating technical insights into business value. Experience in AI governance, ethical frameworks, and regulatory compliance. Skills: Advanced proficiency in data science techniques, including machine learning, optimisation, simulation, deep learning, and generative AI. Comprehensive understanding of the mathematical foundations underpinning AI algorithms. Strong stakeholder engagement and relationship-building ...

opportunities, and change management. What You Bring Expertise in cloud platforms (AWS, Azure, GCP) and multi-cloud integration. Deep understanding of large language models, machine learning frameworks, and AI architectures. Proficiency in programming languages (Python, Java, C#). Strong analytical and problem-solving skills for complex system design. ...

right here at Sky. What you'll do Design and implement scalable APIs and backend services, primarily in Scala, to integrate ML models into production systems and deliver personalised experiences. Real time data processing and gRPC microservices (Typelevel stack). Take end-to-end ownership of services, from development …/improving automated pipelines that support our Continuous Delivery process Build, scale and maintain large scale cloud-based services Work closely with data scientists, ML engineers, and product teams to align technical solutions with business goals. Refining the team processes to continuously integrate and working towards a continuously deliverable application. ...

right here at Sky. What you'll do Design and implement scalable APIs and backend services, primarily in Scala, to integrate ML models into production systems and deliver personalised experiences. Real time data processing and gRPC microservices (Typelevel stack). Take end-to-end ownership of services, from development …/improving automated pipelines that support our Continuous Delivery process Build, scale and maintain large scale cloud-based services Work closely with data scientists, ML engineers, and product teams to align technical solutions with business goals. Refining the team processes to continuously integrate and working towards a continuously deliverable application. ...

right here at Sky. What you'll do Design and implement scalable APIs and backend services, primarily in Scala, to integrate ML models into production systems and deliver personalised experiences. Real time data processing and gRPC microservices (Typelevel stack). Take end-to-end ownership of services, from development …/improving automated pipelines that support our Continuous Delivery process Build, scale and maintain large scale cloud-based services Work closely with data scientists, ML engineers, and product teams to align technical solutions with business goals. Refining the team processes to continuously integrate and working towards a continuously deliverable application. ...

right here at Sky. What you'll do Design and implement scalable APIs and backend services, primarily in Scala, to integrate ML models into production systems and deliver personalised experiences. Real time data processing and gRPC microservices (Typelevel stack). Take end-to-end ownership of services, from development …/improving automated pipelines that support our Continuous Delivery process Build, scale and maintain large scale cloud-based services Work closely with data scientists, ML engineers, and product teams to align technical solutions with business goals. Refining the team processes to continuously integrate and working towards a continuously deliverable application. ...

right here at Sky. What you'll do Design and implement scalable APIs and backend services, primarily in Scala, to integrate ML models into production systems and deliver personalised experiences. Real time data processing and gRPC microservices (Typelevel stack). Take end-to-end ownership of services, from development …/improving automated pipelines that support our Continuous Delivery process Build, scale and maintain large scale cloud-based services Work closely with data scientists, ML engineers, and product teams to align technical solutions with business goals. Refining the team processes to continuously integrate and working towards a continuously deliverable application. ...

right here at Sky. What you'll do Design and implement scalable APIs and backend services, primarily in Scala, to integrate ML models into production systems and deliver personalised experiences. Real time data processing and gRPC microservices (Typelevel stack). Take end-to-end ownership of services, from development …/improving automated pipelines that support our Continuous Delivery process Build, scale and maintain large scale cloud-based services Work closely with data scientists, ML engineers, and product teams to align technical solutions with business goals. Refining the team processes to continuously integrate and working towards a continuously deliverable application. ...