Senior ML Architect-Scientist, Telemetry and Log Analytics

Dell
Cork, IrelandPosted 10 April 2026

Job Description

Senior ML Architect/Scientist – Telemetry and Log Analytics Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, our mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand new methodologies, tools, statistical methods, and models. What’s more, we are in collaboration with leading academics, industry experts and highly skilled engineers to equip our customers to generate sophisticated new insights from the biggest of big data. Join us to do the best work of your career and make a profound impact as Senior ML Architect/Scientist, Telemetry & Log Analytics on our growing and dynamic team in Ireland. What you’ll achieve In the role as a Senior ML Architect/Scientist, you will lead the modelling strategy and analytic architecture that transform how we extract value from telemetry and log data. You will be responsible for defining reference architectures, modelling blueprints, and evaluation frameworks for time‑series and event-based telemetry across batch and streaming . You will guide the selection of algorithms, shape data and feature architectures, and partner with engineering teams to deliver solutions that improve reliability, accelerate root‑cause analysis, and elevate customer experience. This role requires an individual capable of translating strategic goals into tangible, high‑impact ML designs, fostering a culture of connection, innovation, and excellence within a dynamic, collaborative environment. You will Own the end‑to‑end modelling strategy and analytic architecture for telemetry/log analytics, from problem framing to deployment, ensuring solutions are robust, scalable, observable , and aligned with product and platform needs Design and specify models for time‑series and event logs including anomaly detection, forecasting, change‑point detection, pattern mining, correlation analysis, root‑cause analysis (RCA), and NLP for unstructured logs Define requirements and architectural patterns for batch and real‑time streaming analytics (e.g., data contracts, schemas/ontologies for metrics/logs/traces, feature stores, and model serving patterns), collaborating with data and platform engineering for implementation Stay current with the latest ML, time‑series, and observability advancements and proactively apply new technologies to enhance team projects and committed to drive innovation Be a thought leader by inspiring and driving innovation, promoting, and supporting best practices, and mentoring the development of IPs, research publications and white papers Take the First Step Towards Your Dream Career Every Dell Technologies team member brings something unique to the table. Here’s what we are looking for with this role: Essential Requirements: 10 years’ experience of applied science or complex software systems, especially involving machine learning and analytic architecture, with production impact on telemetry/log or observability data Proven expertise across relevant modelling techniques: anomaly detection, forecasting, change‑point detection, pattern mining, correlation analysis, root‑cause analysis, and NLP for logs (template mining, embeddings, topic modelling, classification) Strong proficiency in Python, SQL and ETL pipelines (Airflow preferred), with deep knowledge of feature engineering for time‑series and event data, statistical validation, and experimental design Familiarity with observability ecosystems (e.g., ELK/Elastic, Splunk, Azure Monitor, Datadog, Grafana/Loki, OpenTelemetry) and how to model, index, and query logs/metrics/traces for ML use cases • Practical leadership in model governance and MLOps standards (data/model versioning, evaluation & monitoring specifications, drift detection requirements, documentation and model risk considerations), with an emphasis on definition and oversight rather than hands‑ ... (truncated, view full listing at source)
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