9 of 9 Permanent Use Case Jobs in Basingstoke

capabilities and benefits of our solution Requirements & Backlog Management Engage with internal stakeholders, partners, and customers to capture, refine, and prioritize AI use cases Translate complex AI concepts into clear epics, features, and user stories aligned with business value Maintain a transparent and prioritized backlog in JIRA Ensure ...

within the organization. Key Responsibilities • CI/CD Pipeline Development: Create and implement new, customized CI/CD pipelines tailored for specific project use cases, ensuring efficient, automated workflows • Pipeline Maintenance: Regularly update and maintain existing CI/CD pipelines to ensure they are efficient, secure ...

level Salesforce Field Service transformation with the autonomy to lead real delivery. You'll work with experienced peers, world-class clients, and interesting use cases that push your technical and leadership abilities. If you're passionate about solving real-world problems, guiding teams, and turning complex requirements into ...

hands-on work with security platforms, scripting tasks, and collaborating with experienced security professionals. Key Areas of Work Enhancing alert logic and monitoring use cases within SIEM platforms Building and maintaining automation workflows using Python Reviewing security events and log data to spot unusual activity Supporting the design ...

prompt engineering strategies for LLM-based features, including few-shot learning, chain-of-thought reasoning, and retrieval-augmented generation Optimize models for specific use cases and performance requirements Design and optimize database schemas for relational database Collaborate with stakeholders to translate business requirements into technical solutions What ...

that simplifies how organisations deploy, manage, and operate AI/ML workloads across Kubernetes environments. The product is designed for performance-critical AI use cases, enabling customers to run GPU-accelerated workloads at scale with reliability and efficiency. About the Role The AI Technical Support Engineer will support ...

UK. Key Responsibilities 1. Machine Learning Model Development Design, develop, train, and evaluate machine learning models for prediction, classification, recommendation, or automation use cases. Apply supervised, unsupervised, and deep learning techniques as appropriate. Perform feature engineering, model tuning, and validation to improve accuracy and performance. 2. Productionisation & Deployment … Ensure data quality, reproducibility, and versioning. 4. MLOps & Automation Implement MLOps practices including CI/CD for ML, model versioning, and experiment tracking. Use tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML. Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure Build ...

collaboratively with the team to ensure project deadlines are met. Design, prototype, and deploy Generative AI models (LLMs, Transformers, Diffusion models) for enterprise use cases. Build and fine-tune LLM-based applications (chatbots, summarization, document Q&A, report generation, code assistants, etc.). Apply prompt engineering, RAG (Retrieval … text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (Pinecone, Weaviate, FAISS, Chroma) for semantic retrieval use cases. Partner with business stakeholders to identify and shape AI use cases. Contribute to the creation of a strategic AI adoption roadmap ...

MLflow, Azure, Docker, Kubernetes. Salary: Up to £100k Working Environment: Fully Remote in UK What you'll do Research, prototype, and deploy LLM use cases (Q&A, summarisation, document processing) Build and tune models using scikit-learn, PyTorch, TensorFlow/Keras, and XGBoost Create data pipelines for batch … streaming with Spark and Kafka Use Databricks and MLflow for experiments, deployment, and monitoring What you'll bring Hands-on Python for data science and ML Practical experience with LLM frameworks (e.g. LangChain) Familiar with Spark/Kafka and End-to-end pipeline experience Databricks, MLflow, Docker, Kubernetes ...