5 of 5 Permanent Low Latency Jobs in Edinburgh

systems and DevOps engineering experience. Basic qualifications 7–10 years building production backend systems, including 3–5 years in high-scale and/or low-latency environments. Deep expertise in Linux networking data path and kernel-level networking (e.g., XDP, eBPF, dpdk, iptables, nftables) for traffic processing, filtering … from prototype to GA. Collaborative, inclusive culture emphasizing design docs, code reviews, and knowledge sharing. What you'll do Lead architecture and delivery of low-latency backend services for DDoS detection, classification, and mitigation. Define and evolve scalable data/control planes (policy, signaling, telemetry, orchestration) with strong ...

technical foundation for customer-facing DDoS capabilities. Basic qualifications 6+ years building production backend systems (at least 3 years in high-scale or low-latency environments). Proficiency in one or more: Java/Python/C Rust/Go Strong preference for Java for control-plane/… gates from prototype to GA. Collaborative, inclusive engineering culture with code reviews, design docs, and knowledge sharing. What you'll do Design and build low-latency backend services for DDoS detection, classification, and mitigation across OCI's global edge. Implement scalable data and control planes (policy, signaling, telemetry ...

driven forecasting and anomaly detection Connect edge to cloud , designing robust APIs and drivers using protocols such as OCPP, Modbus, and CAN , with secure, low-latency data pipelines Collaborate on data visualisation , supporting intuitive dashboards and reports that drive operational and commercial decisions Ensure security & reliability , implementing high ...

systems. Ideal for someone who thrives in fast-paced, trading-led environments where precision and performance are non-negotiable. Key Responsibilities Build and maintain low-latency distributed data pipelines Develop and run real-time time-series data collectors Automate monitoring and data quality checks Create tools and APIs ...

advanced machine learning and deep learning models into production. Architect scalable LLMOps pipelines on GCP/Vertex AI, including fine-tuning, vector search, and low-latency inference. Build end-to-end LLM applications, leveraging RAG (Retrieval-Augmented Generation), agentic workflows, and prompt engineering. Implement robust evaluation frameworks ...