18 of 18 Permanent Error Analysis Jobs in the UK

deterministic software, machine learning, large language models, human review, or a combination of approaches. Establish evaluation-driven development practices, including test datasets, error analysis, deterministic checks, model-based evaluation, and business outcome measurement. Ensure solutions meet production requirements for reliability, observability, scalability, latency, maintainability, security, and cost. Guide … model evaluation. Experience grounding AI systems in enterprise data, including structured data, documents, semantic models, vector stores, or knowledge graphs. Experience establishing evaluation and error-analysis practices for systems with probabilistic outputs. Ability to balance model quality, reliability, latency, cost, security, and user experience. Experience with cloud-native ...

loop experiences, and operational controlsDefine validation approaches and success measures for AI and ML products, using appropriate offline and online metrics, experimentation, quality thresholds, error analysis, and business impact measuresUse customer, campaign, and product data to identify opportunities, evaluate performance, make technical and product trade-offs, and continuously … products, MLOps, observability, and reliabilityExperience defining evaluation and validation frameworks for AI or ML products, including offline metrics, online experimentation, human evaluation, quality thresholds, error analysis, and guardrailsExperience building or productizing agentic systems, intelligent workflows, recommended systems, optimization systems, decision engines, or comparable AI-enabled platforms; able ...

experiences, and operational controls Define validation approaches and success measures for AI and ML products, using appropriate offline and online metrics, experimentation, quality thresholds, error analysis, and business impact measures Use customer, campaign, and product data to identify opportunities, evaluate performance, make technical and product trade-offs … MLOps, observability, and reliability Experience defining evaluation and validation frameworks for AI or ML products, including offline metrics, online experimentation, human evaluation, quality thresholds, error analysis, and guardrails Experience building or productizing agentic systems, intelligent workflows, recommended systems, optimization systems, decision engines, or comparable AI-enabled platforms; able ...

architect calibrated LLM-as-a-judge pipelines, and build metrics that accurately capture multi-step agent performance under non-deterministic conditions. Your insights and error analyses will directly drive iterative improvements to our harness scaffolding, tool orchestration, and system safety guardrails. What you’ll do: Architect Evaluation Runtimes & Harnesses … latency, and variance across multi-step agentic systems. Design Experiments & Validate Results: Apply rigorous statistical methods—including hypothesis testing, confidence intervals, bootstrapping, and power analysis—to determine whether performance changes are true system improvements or stochastic noise. Build & Calibrate LLM-as-a-Judge Pipelines: Develop automated judging systems validated ...

possible, and communicating useful findings clearly. You will support senior R&D, Data Programme and AI colleagues while taking meaningful ownership of exploratory data analysis, data profiling, analytical prototyping and the measurement of data and AI products. You will join a small, hands‐on multidisciplinary team working collaboratively across … workspaces, build reproducible analyses and create clear visualisations and summaries for technical and business audiences. Form and test hypotheses; identify where further data, enrichment, analysis or modelling could create additional value for an R&D product or business question. Support the development and evaluation of baseline statistical and machine ...

possible, and communicating useful findings clearly. You will support senior R&D, Data Programme and AI colleagues while taking meaningful ownership of exploratory data analysis, data profiling, analytical prototyping and the measurement of data and AI products. You will join a small, hands-on multidisciplinary team working collaboratively across … workspaces, build reproducible analyses and create clear visualisations and summaries for technical and business audiences. Form and test hypotheses; identify where further data, enrichment, analysis or modelling could create additional value for an R&D product or business question. Support the development and evaluation of baseline statistical and machine ...

that benchmark outputs against plot inventories and third‐party reference datasets, quantify uncertainty, and surface failure modes; produce QA artefacts (maps, plots, model cards, error analyses) that internal teams and clients can trust and defend. Partner with Engineering to take models into scalable, reproducible inference pipelines across millions ...

more relevant technical tools such as: MATLAB Python RSolidWorks AutoCAD SPICE GIS platforms Chromatography software Spectroscopy software Other discipline-specific engineering or scientific analysis tools Analytical Skills: Strong understanding of: Experimental design Measurement uncertainty and error analysis Statistical reasoning Data interpretation Scientific methodology Common analytical and statistical ...

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 ...

operational problems using data, technical tools, and strong judgment. You will work as an experienced individual contributor across USRO, moving from problem definition through analysis, workflow design, implementation, measurement, and handoff. The scope is intentionally broad and may span emerging-risk detection, operational quality, automation, launch readiness, and other … workflows while independently validating outputs and managing failure modes. Understand how to measure technical or operational systems using concepts such as precision, recall, coverage, error analysis, quality assurance, and human review. Exercise sound judgment in scaled operations, including queues, escalations, reviewer workflows, capacity, quality, and incident response. Move ...

related field. Engineering depth: Strong ability to turn research ideas into working, scalable systems — not just notebooks. Experimental rigour: Evaluation design, ablations, error analysis, and careful interpretation of results are how you work, not afterthoughts. Production experience: You have shipped and operated AI or machine learning systems ...

requires hands-on experience with Python and ML frameworks (PyTorch/TensorFlow), production ML pipelines, and GPU optimisation, with emphasis on rigorous evaluation and error analysis. #J-18808-Ljbffr ...

TypeScript.Practical experience with modern ML and LLM systems, including structured outputs, retrieval, tool use and evaluation.Strong understanding of experimental design, model limitations and systematic error analysis.Experience building and operating cloud services, including testing, observability and AI/ML operations.Ability to translate ambiguous requirements into clear technical approaches and reliable ...

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

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 ...

Implement AT-TLS rules (digital certificate management). Configure and manage IPSEC policies (permit/deny rules, VPN- ipsec tunnels) Trace, Debug and Error Analysis Communicate regularly with technical, applications and operational staff to ensure Network connectivity and security (may involve some after hours and weekend work ...

support on reports developed to the business teams to ensure user adoption. Ensure accuracy, consistency, and timeliness of financial data, including data checking and error analysis. Being the point of contact for answering data related queries and clarifications. Identify opportunities to automate reporting and improve data processes. Skills & Experience ...

quality checks, lineage, provenance, observability, monitoring and change management within Fabric and Databricks workflows so data assets remain trusted over time. Conduct exploratory data analysis to surface patterns, gaps, anomalies and data-quality issues, and identify opportunities for analysis, modelling or product use. Develop, compare and validate appropriate … data-quality monitoring. Run EDA and model development that increases the value of priority data assets for client intelligence, opportunity identification, pricing, matter analysis and other high-value use cases. What Success Looks Like The Data Programme and R&D teams can use documented, quality-controlled data assets ...