8 of 8 Machine Learning Jobs in West End of London

Sentiment Analysis ProjectWork with Hugging Face to build a sentiment analysis classifier using real-world AI techniques.Step 8 – AI Prompt EngineeringMaster 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 using … Chatbot ProjectCombine 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 FundamentalsUnderstand machine learning principles and algorithms, and how to train and test models using scikit-learn.Step 12 – Machine 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 ...

engineering environment. Required: Core experience Strong grounding in audio machine learning or applied signal processing Experience training and evaluating models using modern ML tooling Awareness of real-world acoustic challenges such as noise, reverberation, and variability Comfort working in a small, fast-moving engineering team Likely … + some industry experience Beneficial Edge or embedded ML optimisation Audio feature extraction or DSP knowledge Postgraduate study in a relevant technical discipline Experience with sensing, monitoring, or real-world data systems ...

based systems, artificial intelligence, and machine learning, with considerable in-depth knowledge in implementing solutions using AWS. Deep understanding of AI/ML solutions implementation, with emphasis on LLM applications and retrieval-augmented generation. Practical cloud-native experience, specifically with AWS (compute, storage, networking, IAM, KMS, observability). … also required to lead the team of 4 who can demonstrate a background in the following: Technical leadership and architecture Delivery ownership AI/ML solution stewardship People leadership Stakeholder and product partnership Controls and governance ...

time AI interactions, knowledge retrieval, and automation. Optimize AI-powered UIs to ensure seamless and intuitive user experiences. Work closely with AI researchers and ML engineers to integrate LLMs, Retrieval-Augmented Generation (RAG), and automation into production-ready applications. Ship robust, minimal-dependency code that performs efficiently in enterprise environments. ...

easy-to-use online platform. Step 2: Full-Stack AI Mastery Dive deeper with in-demand technical skills including Python programming, data handling, machine learning, and version control with Git and GitHub. You’ll work on hands-on mini projects that mirror real-world challenges, helping you build ...

through to being qualified to work in a junior Data Scientist role. Through the interactive courses, you will gain knowledge in Python, R, Machine Learning, AI, and much more. You will also complete mini projects to gain practical experience and test your skills while you study. This step ...

secure coding standards. Collaborate with the Head of AI and Technology to align development priorities with business objectives. Foster a culture of collaboration, continuous learning, and high performance within the team. Troubleshoot and resolve complex technical issues, ensuring platform reliability and uptime. Required Skills & Qualifications: 8+ years of commercial … design. Hands-on experience with AWS platform. Excellent communication skills, capable of motivating and aligning technical teams. Experience with AI tools, APIs, or ML pipelines is highly desirable. Bonus: Exposure to startup environments. Benefits: Hybrid working model (minimum 3 days a week in office) 25 days annual leave plus bank ...