1 to 25 of 94 Machine Learning Jobs in the North West

reliability, and performance Partner closely with data scientists to turn experimental models into well-engineered, production-ready systems Develop and maintain end-to-end ML pipelines, including feature engineering, training, evaluation, versioning, monitoring, and automated retraining Contribute to MLOps capabilities, including CI/CD pipelines, model registries, infrastructure automation … fairness analysis, and performance optimisation Collaborate with data engineers and architects to enhance data quality, data flows, and platform capabilities Lead experimentation using modern ML frameworks to assess new algorithms and technologies and make recommendations on adoption Support model governance processes, ensuring compliance with internal standards, documentation, transparency, and regulatory ...

model capability. THE ROLE As a Staff Machine Learning Engineer you will... Lead the design, development, and deployment of end-to-end ML solutions. Architect scalable ML systems and pipelines that integrate seamlessly with cloud infrastructure. Mentor engineers, championing best practices across coding, experimentation, and MLOps. Collaborate with … Product and Engineering teams to define priorities and model strategy. Apply deep learning, NLP or classical ML techniques to real-world, high-impact problems. Uphold responsible AI principles across model development and evaluation. YOUR SKILLS & EXPERIENCE The successful Staff Machine Learning Engineer will have: Strong Python skills ...

Junior ML Operations Engineer (Python) Salary: Up to £40,000 depending on experience Location: Manchester - (Hybrid working - currently 40% on site increasing to 60% within 12 months) Ref: J13059 This is an exciting opportunity to build a career in production machine learning within a large scale pricing … will be supported by experienced engineers, exposed to modern tooling, and given the space to build confidence in production machine learning and ML Operations. This role is designed to set strong foundations for long term technical growth. Right to work You must be eligible and authorised to work ...

ensuring your CV and skills are a good match. Working on a strategic Lakehouse platform built on Databricks, you will influence how production ML models are designed, governed and optimised, helping the business turn complex data into reliable, decision-driving insight. The role combines hands-on engineering with MLOps leadership … governance, access control, monitoring and retraining strategies * Develop automated model validation tests covering unit, integration, regression and bias checks * Translate business problems into effective ML solutions, managing ethical, privacy and data governance considerations * Establish model performance KPIs, reliability measures and production monitoring frameworks * Document model design, assumptions, metrics, risks ...

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/ ...

delivering advanced language and AI solutions to clients. The Role Lead and architect large-scale machine learning projects Build and deploy scalable ML models, pipelines, and systems Mentor engineers and set technical direction across teams Drive innovation through research and adoption of new ML techniques Present technical insights … Machine Learning Engineering or similar senior roles Strong Python skills; experience with deep learning frameworks (TensorFlow, PyTorch) Solid understanding of ML algorithms, statistics, and data modelling Experience with large-scale data tools (Hadoop, Spark, Kafka) Cloud & MLOps experience (AWS, Azure, or GCP) NLP experience highly beneficial Strong ...

computer vision systems deployed into real-world environments. This role is technical and delivery-led. It would suit someone with strong applied coding and ML experience who has spent several years working in production, customer-facing environments, ideally with deep computer vision expertise and a clear track record of deploying … supporting, and iterating on live ML systems, rather than purely experimental or proof-of-concept work. If you come from a vehicle, manufacturing, or industrial automation background, with experience deploying computer vision or ML systems into live production environments, this would be a strong advantage. Key Responsibilities Design, build, deploy ...

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 ...

Machine Learning Engineer - Research Team Join the research arm of a leading gaming organisation to develop cutting-edge AI solutions that transform game quality assurance. This role focuses on automating … testing by building intelligent agents that detect anomalies and glitches in gameplay, ensuring an exceptional player experience. Key Responsibilities Design and implement ML models for anomaly detection in video streams and gameplay data. Apply computer vision and video analysis techniques to identify irregularities and bugs. Explore advanced methods such ...

, and operations research (linear, mixed integer programming, heuristics) Fluent in Python(required) and other programming languages (preferred)with strong skills in applying DS, ML, and OR packages (scikit-learn, pandas, numpy, gurobietc.) to solve real-life problems and visualise the outcomes (e.g. seaborn) Proficient in working with cloud platforms … preferred), code versioning (Git), experiment tracking (e.g. MLflow) Experience with cloud-based ML tools (e.g. SageMaker), data and model versioning (e.g. DVC), CI/CD (e.g. GitHub Actions), workflow orchestration (e.g. Airflow/Dagster) and containerised solutions (e.g. Docker, ECS) nice to have Experience in code testing (unit, integration ...

Title: Machine Learning Engineer - Computer Vision (Contract) Location: UK Remote/Hybrid Day Rate: 4-600 per day Why Apply? All the relevant skills, qualifications and experience that a successful applicant will need are listed in the following description. This contract offers the opportunity to take full technical … ownership of a high-impact computer vision workstream focused on real-world AI deployment. You will lead the development and improvement xxuwjjq of machine learning models that detect damage on large commercial vehicles u... ...

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 ...

large-scale data processing, machine learning and next-generation search experiences. In this role, you will lead multiple engineering teams across data, ML, web, QA and DevOps disciplines to deliver a platform that processes massive datasets, powers complex distributed systems and provides high-value insights to enterprise clients. … processing, machine learning pipelines and web application development Ensure systems are scalable, reliable and capable of handling large-scale data and evolving ML workloads Introduce and measure engineering KPIs Drive improvements in delivery processes, release quality and development efficiency Collaborate with Product to prioritise work and align delivery ...

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 ...

ML Engineer Location: Chester (Hybrid - 2x week in office) Salary: £70,000 - £80,000 About the Role I'm working with an established company who are looking to bring an ML Engineer into their team. You will report into the Head of Platform Engineering and work closely with data scientists … paced, high-impact environment. What You’ll Be Doing Operationalising machine learning models and ensuring they are production-ready Supporting AI/ML initiatives focused on revenue management, including pricing and elasticity models Contributing to churn and revenue prediction use cases Working on conversational AI, including ...

Senior ML Operations Engineer (Python) Salary: Up to £66,000 depending on experience Location: Manchester - (Hybrid working - currently 40% on site increasing to 60% within 12 months) Ref: J13060 We are seeking a Senior ML Operations Engineer to take ownership of how machine learning models are deployed … impact sits in the middle, where strong engineering judgement meets real world business outcomes. What you will do Own and improve Python based ML and pricing deployments Build and maintain shared deployment tools and frameworks Enable controlled and repeatable model releases Work closely with engineers, analysts and stakeholders Influence technical ...

organisation with a reputation for excellence and a supportive, inclusive culture, is seeking a Lead Data Platform Engineer to join their Data Engineering and Machine Learning team. This is a high-impact, senior role, ideal for someone with deep experience in modern cloud data platforms, looking to shape … experience with CI/CD, automation, and infrastructure-as-code (Terraform, ARM templates) is essential. Experience in machine learning platforms or ML engineering is a bonus. Key Responsibilities: Build and maintain the Data Lakehouse platform in a secure Azure environment Develop automation for cluster management, integration runtimes ...