9 of 9 Error Analysis Jobs in the UK

interaction.JOB DUTIES AND RESPONSIBILITIESDefine, design, implement, and maintain measurement/test solutions for link/modem validationDefine and analyze calibration and metrology aspects (statistical error analysis, confidence levels, error budgets)Develop modular, reusable software in Python (or similar languages) to be implemented in a variety of setupsAnalyze … layer satellite modem algorithms/standards (DVB-S2, CCSDS)Experience in collaborative software design (GIT, code reviews)Experience in test automationLinux and Windows experienceStatistical analysis and metrologyCesiumAstro considers several factors when extending an offer, including but not limited to, the role and associated responsibilities, a candidate’s work experience ...

appropriate use of metrics for model quality, retrieval quality, ranking performance, data accuracy, user outcomes, and business impact.Guide offline evaluation, A/B testing, error analysis, annotation workflows, and human-in-the-loop evaluation where needed.Promote responsible AI practices, including transparency, fairness, bias assessment, explainability, privacy, and risk … information retrieval, or applied AI.Experience managing or leading technical teams directly.Strong understanding of data science methods, including supervised and unsupervised learning, Gen AI, statistical analysis, model evaluation, and experimentation.Practical experience with Python and common data science, machine learning, or NLP frameworks.Experience working with large, complex, structured and unstructured datasets.Ability ...

metrics for model quality, retrieval quality, ranking performance, data accuracy, user outcomes, and business impact. Guide offline evaluation, A/B testing, error analysis, annotation workflows, and human-in-the-loop evaluation where needed. Promote responsible AI practices, including transparency, fairness, bias assessment, explainability, privacy, and risk management. … retrieval, or applied AI.Experience managing or leading technical teams directly. Strong understanding of data science methods, including supervised and unsupervised learning, Gen AI, statistical analysis, model evaluation, and experimentation. Practical experience with Python and common data science, machine learning, or NLP frameworks. Experience working with large, complex, structured ...

deepen understanding of AR waveguide physicsBuild and apply models of optical and physical phenomena to interpret lab experimentsDesign, build, and automate optical setupsRun experimental analysis of waveguides using both proprietary and commercial toolsPerform root cause analysis of failures of waveguide displaysPerform experiments on diffractive nanostructures to make improvements … optics, imaging, radiometry, photometry, colorimetry, statistics etc.)Solid understanding of polarization theory and experimental techniquesExperience with interferometry and phase retrieval methodsStrong scripting and data analysis skills in Python (or similar)Proficient in error analysis of experimentsExperience working in an optical lab environment, hands-on experience setting ...

reliably different models identify changes in a market narrative, improving entity resolution across millions of documents, designing an agentic workflow for automated market analysis or reducing the latency of a production intelligence pipeline. What you’ll do Build production AI systems Design, build and deploy LLM and NLP pipelines … headline benchmark performance. Work with proprietary datasets Train and evaluate models against Permutable’s large-scale historical and real-time datasets. Carry out detailed error analysis and use what you find to improve model and system performance. Build reliable ML infrastructure Develop and maintain data and machine learning ...

robust evaluation datasets, metrics, and validation frameworks. Build and deploy classification, matching, and inference models for production use. Measure model performance and produce detailed error analysis to support ongoing improvement. Apply LLMs in appropriate use cases such as extraction, constrained labelling, and code generation, supported by clear evaluation ...

agents, including MCP/tool abstraction, credential management and enterprise API integration. Contributing to AgentOps and GenAIOps capabilities, including telemetry, run history, task outcomes, error analysis and feedback loops Contributing to reliability patterns for production AI systems, including latency monitoring, alerting, scaling considerations and operational readiness. Applying ...

evaluation set design, and metric definition. Build and deploy production classification models and matching or inference models. Measure, document, and communicate model performance, including error rates and error analysis. Apply LLMs appropriately for tasks such as extraction, constrained labelling, and code generation, supported by rigorous evaluation frameworks. Contribute ...

plants, supply chains, material grades Build baselines, then define evaluation sets and metrics before modelling Ship classifiers and matching/inference models with measured error rates and written error analyses Use LLMs where they genuinely belong — extraction, constrained labelling, code generation — with proper evals, never open-loop guessing ...