11 of 11 Machine Learning Jobs in Newcastle upon Tyne

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 ...

Virtual Agent - our conversational interface that helps colleagues get support quickly through automated chat - used by around 120,000 colleagues. You'll use machine learning, analytics and data engineering skills to solve complex problems, reduce manual effort, and directly influence how services perform at scale. This role offers … need? Strong experience with Python (core programming language), along with common data science libraries such as Pandas, NumPy and SciKit-Learn Experience applying machine learning and AI techniques (classification, clustering or regression) to real problems, ensuring solutions are robust and meet the intended business outcome Familiarity with Jupyter ...

Deploy, monitor, and manage machine learning models in production Automate model training, testing, and deployment workflows Ensure scalability, reliability, and security of ML systems Collaborate with data scientists and engineering teams to productionise models Troubleshoot and optimise existing ML pipelines Required Skills & Experience Strong hands-on experience with … SageMaker Solid understanding of MLOps best practices Experience with CI/CD pipelines for ML workloads Proficiency with Python and relevant ML frameworks Experience working in cloud-based environments (AWS) Security Requirements Active SC Clearance ...

Responsibilities Data Acquisition & Preparation : Source, create, collect, clean, transform, and structure data for analysis and operational use, including synthetic data generation. Build and productionise ML/NLP solutions for legal and business use cases to enable better decision making. Feature Engineering & Integration : Develop new features, integrate data from internal/… build scalable and efficient data pipelines Ability to design, build, and deploy data solutions that explore, capture, transform, and utilise data to support AI, ML, and BI Proficiency in data science languages/tools such as R, Python, SAS Awareness of ITIL (Incident, Change, Problem management) #LI-JC1 Diversity, Equity ...

Spark, and Delta Lake Build and optimize ETL/ELT workflows for batch and streaming data Develop data models to support analytics, reporting, and machine learning use cases Ensure data quality, reliability, and performance across … data platforms Integrate data from multiple sources including APIs, databases, and cloud storage Collaborate with data scientists and analysts to enable advanced analytics and ML workloads Implement monitoring, logging, and cost-optimization best practices Follow data governance, security, and compliance standards Document data pipelines, architectures, and best practices Required Qualifications ...

engineering, and analytics, translating strategic goals into clear product outcomes and actionable backlogs. You'll own the roadmap for data products that enable analytics, machine learning, and data-driven decision-making at scale. Key Responsibilities Own and manage the product vision, roadmap, and backlog for data platform capabilities … Ensure data products are scalable, secure, cost-efficient, and aligned with best practices Drive adoption and value realisation of Databricks (e.g. data engineering, analytics, ML use cases) Collaborate with engineering teams to plan sprints, manage dependencies, and remove blockers Balance short-term delivery with long-term platform strategy Monitor platform ...

data governance frameworks. Experience complying with data security requirements. Experience designing data models. Excellent problem-solving, communication, and documentation skills. Familiarity with AI/ML data pipelines and analytics platforms. Preferred Qualifications: Experience with cloud data platforms (e.g., AWS, Azure, Google Cloud). Experience with big data technologies (e.g., Hadoop ...

Spark, Kafka) Familiarity with ETL/orchestration tools (e.g. Informatica, Talend, Airflow) Experience with API integration and microservices data flows Familiarity with AI/ML data pipelines or analytics platforms Experience using UML/SysML Security Requirements Due to the nature of the work: Candidates must hold active SC clearance ...

Data+ certification and enables you to demonstrate your knowledge in advanced data processing, cleaning, and statistical modelling concepts. You will demonstrate your knowledge of machine learning, industry trends and use of specialised data science applications. You will also apply mathematical and statistical methods appropriately. Step ...

above) Expertise with C++ and Python is essential Experience with Linux and real-time software development Expertise with robotics, automation or machine control Basic electronics knowledge and ability to read schematics Familiarity with ROS, OpenCV, machine learning or PLC software is a plus Eligibility for UK defence ...

IR35) Role Overview We are seeking an experienced MLOps Engineer with strong expertise in AWS SageMaker to support the delivery, deployment, and operationalisation of machine learning models click apply for full job details ...