3 of 3 Permanent Model Validation Jobs in Hampshire

leading hands-on development of models and RAG pipelines to support enterprise-grade LLM applications. MLOps and LLMOps : Build and maintain scalable MLOps and LLMOps pipelines, enabling automation of model training, testing, deployment, and monitoring. Enable reproducibility, traceability, and performance optimization across all AI solutions. Vendor Product Evaluation & Onboarding : Lead the technical evaluation of third-party AI products and … conducting benchmarking, sandbox testing, and assessing integration feasibility. Collaborate with procurement, legal, and security teams to ensure successful onboarding of approved vendors. Governance & Compliance : Define and enforce standards for model validation, bias detection, and explainability, ensuring alignment with internal governance frameworks and external regulations such as GDPR and FCA Platform Enablement: Leverage Databricks, Azure AI, and Microsoft Copilot … while developing reusable AI components, APIs, and Copilot plugins to support business teams and drive adoption.# About You Knowledge Strong understanding of machine learning engineering principles, including pipeline design, model lifecycle management, and production deployment including CI/CD, model registries, and automated workflows while managing feature stores and internal knowledge bases for RAG. Strong grasp of prompt More ❯

data (small-scale and large datasets). Contribute to product development through applied research and quantitative analysis. Perform statistical and coding-based analysis (Python, R, SQL). Support calibration model training and validation for sensor systems. Collaborate across disciplines to develop and deploy new sensing and data technologies. Document research findings and present results to technical and non More ❯

data (small-scale and large datasets). Contribute to product development through applied research and quantitative analysis. Perform statistical and coding-based analysis (Python, R, SQL). Support calibration model training and validation for sensor systems. Collaborate across disciplines to develop and deploy new sensing and data technologies. Document research findings and present results to technical and non More ❯