7 of 7 Machine Learning Jobs in Norfolk

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 ...

using R in conjunction with REST APIs Development and maintenance of Shiny applications Data wrangling, analysis, and automation of analytical workflows Desirable AI/ML: Supporting or deploying AI and machine learning workflows in production environments Integrating analytical or machine learning outputs into existing platforms ...

data science solutions including data ingestion, feature engineering, model development, deployment, and monitoring Define logical and physical architectures for analytics platforms, ML pipelines, and AI products Ensure solutions are scalable, reusable, secure, and cost effective Select appropriate ML/AI techniques (e.g., regression, classification, NLP, forecasting, clustering) 2. Data & Analytics … Development & Deployment Strategy Guide data scientists on: Model selection and evaluation strategies Experiment tracking and reproducibility Design MLOps frameworks for: CI/CD of ML models Model versioning and governance Monitoring drift, accuracy, and bias 4. Technology & Platform Governance Define standards for: Programming languages and frameworks Cloud vs on prem ...

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 ...

awareness programs on data governance Promote a culture of data stewardship and accountability Manage data governance platforms (e.g., Collibra, BigID) Leverage AI/ML tools for automated compliance and classification Monitor compliance and effectiveness of governance policies Present dashboards and reports to senior leadership Your Profile Essential Skills/Knowledge ...

Contract (Inside IR35) Duration: 6 Months Job Summary: Our client is seeking a skilled and innovative Generative AI Engineer to join our AI/ML team. In this role, you will design, develop, and deploy cutting-edge generative models-including LLMs, diffusion models, and GANs-to solve real-world problems … ethical and responsible AI development , including bias mitigation and safety evaluations. Essential Skills, Experience, and Abilities: Strong programming skills in Python and experience with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers). Solid understanding of deep learning, NLP, and generative modeling techniques . Experience with training and fine ...

functional teams to deliver outcomes across Master Data Management (MDM), data integration, data engineering platforms, and discovery/analytics services (BI/AI/ML). This is a delivery leadership role with strong technical depth and executive presence. Ideal for: A seasoned delivery leader who can translate strategy into … data lake/lakehouse, orchestration (Airflow/MWAA), ETL/ELT (e.g., Glue), DQ frameworks. Discovery services: BI/analytics (Power BI/Tableau), ML feature pipelines, self-service data products. Oversee architecture conformance, security/compliance (PII/PHI, GDPR), and cost optimization. Ensure observability (logging/metrics ...