1 to 25 of 291 Machine Learning Jobs in the South East

services and deliver value to its clients. Description Senior Machine Learning Engineer - London This role focuses on training custom models, building robust ML pipelines, and deploying systems at scale from research experimentation through to monitored production services. Design, train, and optimise machine learning models for audio … tasks such as speaker diarization, automatic speech recognition (ASR), and voice activity detection. Build and maintain training and inference pipelines using PyTorch, and related ML frameworks Source, curate, and prepare training datasets; implement preprocessing, augmentation, and validation workflows. Run structured experiments, evaluate model performance, and iterate based on measurable results ...

Data Scientist/Machine Learning Engineer Join our team as a Data Scientist/Machine Learning expert in the Analytics department within the business services industry. This permanent position, based in London, offers an opportunity to apply advanced data science techniques to deliver actionable insights. Client … Learning expert should have: A strong academic background in data science, computer science, mathematics, or a related field. Hands-on experience with AWS ML stack (SageMaker, Lambda, Redshift). Proven ability to design and implement machine learning algorithms and models. Proficiency in Python, SQL, and ML libraries ...

Machine Learning Operations Engineer Our financial services client based in London is looking to recruit a Machine Learning Operations Engineer ASAP. The position will be a Hybrid role be working from home and their offices in London. To be considered for the role you must have … within the company. Technical Skills required Previous experience in designing, building, optimising, deploying and managing business-critical machine learning models using Azure ML in Production environments. Experience in data wrangling using Python, SQL and ADF. Experience in CI/CD and DevOps/MLOps and version control. Familiarity ...

+ benefits Harnham is working with a tech firm in the Private Equity space and hiring a few positions across Data Science, Machine Learning Engineering and Data Engineering. The company have an impressive founding team and hold a strong reputation within the Data & AI and Private Equity space. … They partner with some leading investment firms in deploying AI and machine learning for the sole purpose of creating value. Often working in ambiguous and greenfield environments, you will collaborate with a strong team of technical people across multiple industries to solve complex commercial and data problems, delivering ...

with prompt engineering, RAG architectures, and multimodal models. Contribute to internal tools for monitoring, testing, and improving AI performance. Stay on the edge of ML/AI research — we give you time and resources to explore, learn, and publish. What We’re Looking For 0–3 years of experience … environment. Is curious, ambitious, and eager to build real AI systems that have an impact. What You’ll Get Hands-on mentorship from senior ML engineers, AI researchers, and founders. Freedom to experiment with state-of-the-art models, tools, and frameworks. Modern tech stack (Python, LangChain, Hugging Face, OpenAI ...

Looking For 0–3 years of experience in Machine Learning, AI, Speech Processing, or Applied Research Strong Python skills and hands-on ML experience Experience with PyTorch, TensorFlow, or Hugging Face Solid understanding of deep learning fundamentals, particularly for sequence and audio models Familiarity with, or strong … architectures Curiosity, strong problem-solving skills, and comfort working in a fast-moving startup environment What You’ll Get Hands-on mentorship from senior ML engineers, AI researchers, and founders Freedom to experiment with state-of-the-art speech and voice models A modern ML stack including Python, PyTorch, Hugging ...

knowledge bases into accessible, searchable, and actionable insights for researchers pushing the boundaries of science. Role Overview We are looking for an AI/ML Engineer who is ready to tackle one of the hardest problems in science: teaching machines to understand chemistry. In this role, you won’t just … monitoring. Knowledge of tools like RDKit or other chemistry specific data toolkits. Familiarity with containerisation of services (Docker/Kubernetes). Publications in relevant ML or scientific journals. What We Offer Competitive salary and a comprehensive benefits package. The opportunity to work on cutting edge research problems at the intersection ...

making that happen. That’s why we’re looking for a Machine Learning Engineer to join our growing AI & ML Engineering team. If you’re excited by the idea of building intelligent solutions that make a real-world impact, this could be the role for you. This … Databricks or Azure Cognitive Services will be a big plus. If you’ve worked on end-to-end Gen AI solutions or have applied ML in retail or ecommerce settings, we definitely want to hear from you. You’ll also need to be a great communicator able to explain complex ...

Data Annotator Analyst – AI/Machine Learning – Expedia Group Location: London (hybrid working) Duration: End of 2026 Pay: £223.18/day About the Role We are looking for a Data Annotator/Data Analyst to support the development and evaluation of AI and machine learning solutions. … consistent, and accurate annotations following defined guidelines Analyze annotated data to identify patterns, issues, and opportunities for improvement Work closely with data scientists and ML engineers to refine annotation strategies Use annotation tools (e.g., Label Studio or similar) to manage and review datasets Perform basic data processing and validation using ...

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 ...

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 ...

partners to develop your career and the solutions we deliver for our clients. In this role you will: Solve challenging business problems using advanced machine learning methods such as Deep Learning and quantitative analytics. Understand business requirements and support the development of business cases. Run discovery analytics … identify new and innovative opportunities. Partner with developers and engineers to deploy machine learning algorithms to deliver business value. Define approaches to embed and scale machine learning models. Build reusable assets, solutions and develop best practices for current and future business problems. Consult on complex analyses ...

optimising, and deploying AI solutions in a fast-moving environment. You’ll work closely with product, data, and engineering teams to design and implement machine learning models, contribute to production-ready pipelines, and help scale AI capabilities across the business. Key Responsibilities: Design, build, and deploy machine … quality, testing, and scalability Required Experience: Proven experience as an AI Engineer or Machine Learning Engineer Advanced Python skills with experience in ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn) Strong understanding of machine learning algorithms and applied AI Experience deploying models into production environments Comfortable working ...

someone who enjoys technical depth, variety, and ownership, and who is comfortable applying the right techniques to each problem - from statistical analysis through to machine learning and deep learning models. You’ll join a small, high-calibre team that values autonomy, flexibility and technical excellence. The environment … actionable data science solutions. Owning the full data science lifecycle, from data ingestion and feature engineering through to modelling, evaluation and deployment. Developing statistical, machine learning and deep learning models to support high-impact, real-world decision making. Working with large, structured and unstructured datasets, combining ...

used across entertainment, engineering, and scientific applications. This role focuses on maximising GPU-based processing performance, including real-time data handling, image processing, and machine learning workloads. You will join a collaborative software engineering team and work closely with machine learning and research specialists … implement high-performance algorithms using CUDA Manage host–device interactions, including memory management, data transfer optimisation, and multi-GPU support Deploy and optimise machine learning models using TensorRT within C++ applications Profile and optimise GPU workloads using NVIDIA Nsight Systems and Nsight Compute Configure GPU hardware and software ...

prior professional experience is required—what matters is curiosity, problem-solving skills, and passion for AI. What You’ll Do Implement, train, and optimize ML models (supervised, unsupervised, reinforcement learning) Preprocess data, engineer features, and evaluate model performance Deploy models to production and monitor performance Collaborate with cross-functional … teams to integrate AI solutions Learn and apply the latest ML/AI research and tools You Should Have Recently completed or soon-to-be completed Bachelor’s or Master’s in Computer Science, Data Science, AI, Statistics, or related field Strong programming skills in Python (and optionally R, Java ...

performant AI-driven features. A Day in The Life Typically Includes: Lead, mentor, and grow a team of engineers focused on AI/ML development within the Infor MES solution. Architect and deliver scalable Generative AI and Machine Learning solutions leveraging Infor OS platform services and APIs. Drive … design and integration of AI/ML models into MES workflows, ensuring seamless customer experiences and operational reliability. Collaborate closely with cross-functional teams — Product Management, Software Engineering, Cloud Infrastructure, and Security — to align AI initiatives with business goals. Evaluate emerging AI/ML technologies and frameworks to continuously innovate ...