1 to 25 of 121 Machine Learning Jobs in the North West

same! Key Responsibilities: Build, maintain, and productionise machine learning models using PyTorch or similar frameworks. Design and optimise data pipelines for ML inference at scale. Work with large datasets using Big Data tools. Deploy ML workflows using AWS infrastructure . Collaborate with data engineers and product teams … integrate ML solutions into RealityMine’s products. Investigate and troubleshoot customer feedback on data quality and drive model improvements from experimentation . Promote best practices in ML engineering and data quality across the business. Adhere to Company Policies and Procedures with respect to Security, Quality and Health & Safety. AI first ...

intersection of machine learning, computational science , and emerging hybrid computing architectures . The work focuses on algorithmic innovation , generative modelling , and benchmarking ML systems on cutting edge hardware platforms. You will contribute to the development of new machine learning algorithms designed for advanced computing systems that … extend beyond traditional GPU/TPU environments. The role involves close collaboration with researchers across ML, physics, and scientific computing, with a strong emphasis on generative models , numerical methods , and hybrid quantum classical approaches . Essential Experience Experience with heterogeneous computing hardware (HPC, NPUs, ASICs, quantum systems). Strong background ...

levels available £45k to £95k DoE plus 15% clearance bonus Must be willing to be full-time on-site in Manchester Skills required in machine learning, GenAI, NLP, Customer Engagement/Consultancy Who are we? We are recruiting Junior, Senior and Lead Data Scientists with AI specialism … look forward to hearing from you. KEY SKILLS: Data Science/Data Scientist/AI Engineer/AI/Machine Learning/ML/NLP/GenAI/Stakeholder Engagement/Customer Engagement/AWS/Azure/Cloud/Docker/Kubernetes/CI/CD/ ...

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 ...

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 ...

Intern, you'll work closely with our experienced team of Data Scientists to support the research and development of both traditional and cutting-edge machine learning algorithms for use with current and future product ranges. Here at ITL, we offer Hands-on experience with real-world projects Mentorship … opportunity to experience working with professionals in their chosen field. Your Responsibilities Collaborate with the data science team to design, implement, and optimize Machine Learning models Analyze large datasets to uncover trends, patterns, and insights that drive business decisions Develop and test algorithms for machine learning ...

Title: AI/ML Engineer – Data Science Location: United Kingdom (Remote/Hybrid) Eligibility: Permanent UK Citizenship required Experience: 5–7 years (Mandatory in Data Science/AI-ML) Role Overview We are seeking a skilled AI/ML Engineer – Data Science to design, develop, and deploy scalable machine … Responsibilities - Design, build, and optimize machine learning and deep learning models for real-world applications. - Develop and deploy AI/ML solutions using modern Python-based frameworks. - Implement NLP models and solutions for structured and unstructured data. - Build and maintain production-ready ML pipelines, ensuring scalability ...

rare chance to do exactly that. You ll join a small, high impact team working at the forefront of next generation architectures, developing ML models and techniques that go beyond what s possible on conventional systems. We are working exclusively with a pioneering deep tech organisation whose technology is used … research output, and technical roadmap. You ll collaborate with internal experts, customers, and research partners to turn complex real world problems into high performance ML solutions. Key Responsibilities Develop and benchmark ML algorithms for novel computing hardware Work on generative models (flow, diffusion, GANs) and hybrid quantum classical architectures Translate ...

Automating Machine Learning workflows (training → deployment) with AWS & GitOps Deploying LLMs using Kubernetes & Docker Building infrastructure with Terraform & Helm Monitoring and maintaining ML models with performance alerts and dashboards Supporting CI/CD for ML pipelines Developing production-grade APIs (REST/gRPC) to serve models Collaborating with … DevOps or MLOps roles (ideally in AWS environments) Hands-on with Docker, Kubernetes, and Terraform Strong scripting skills in Python or Bash Familiar with ML lifecycle tools, model monitoring, and versioning Exposure to tools like KServe, Ray Serve, Triton, or vLLM a big plus Bonus Points: Experience with observability frameworks ...

will be working on Designing and building Python applications that sit at the heart of AI solutions Supporting the development and deployment of machine learning systems Turning complex challenges into clean, scalable software Working closely with experienced engineers, data scientists, and consultants Testing, refining, and improving systems … they move into production Learning how high impact AI solutions are delivered to real clients What we are looking for A degree in Computer Science, Software Engineering, AI, Data Science, or a closely related subject A strong academic background from a top university, with Russell Group preferred Confidence writing ...

curious Data Scientist to join our team and help transform complex data into clear, actionable insights that drive business performance. Youll use statistical methods, machine learning, and data visualisation tools to identify trends, solve problems, and support data-driven decision-making across the organisation. In this role, youll … data through clear, engaging dashboards and presentations. Work collaboratively with engineers, analysts, and business leaders to deliver impactful projects. Develop and enhance AI/ML tools, including Google Vertex AI and Azure ML. Stay up to date with emerging tools, technologies, and best practices in data science. Youll measure success ...

delivery of cutting-edge Machine Learning and AI-powered products. This role is ideal for someone who combines strong technical credibility in ML/AI environments with proven leadership and people management skills. You'll oversee delivery pipelines, mentor engineers, and ensure AI-driven products are delivered … standard - on time and aligned to business impact. Key Responsibilities Lead, mentor, and develop a team of engineers working across software and AI/ML initiatives Drive delivery across multiple concurrent projects, ensuring alignment with business and product goals Oversee technical direction, architecture, and best practices across Machine Learning ...

ingestion pipelines from structured and unstructured data sources Integrating predictive models into operational applications used by claims handlers and lawyers Supporting the deployment of machine-learning models into production environments Assisting with CI/CD pipelines to ensure analytics products are stable, scalable, and secure Working alongside … Some experience in software development (academic, placement, or early career) An understanding of APIs and systems integration concepts A strong interest in predictive modelling, machine learning, and analytics Good problem-solving skills and a proactive willingness to learn Desirable Exposure to analytics platforms or machine learning ...

weeks (with potential for extension) Status: Outside IR35 Location: Remote (UK-based) Start Date: ASAP About the Role We are seeking an experienced Data & ML Contractor to deliver a proof of concept using static, structured datasets. This is a focused, pragmatic engagement centred on data preparation, feature engineering, and anomaly … basic data modelling concepts Feature engineering: ability to craft interpretable, business-relevant features Anomaly detection experience: practical knowledge of rule-based and statistical methods; ML-based approaches where appropriate Requirements & communication: ability to work with stakeholders, define success criteria, and explain outputs clearly Desirable (Nice to Have) Power BI/ ...