426 to 450 of 500 Low Latency Jobs in the UK excluding London

Mastery of multiple languages and paradigms; able to guide complex trade-offs and technical decisions Extensive experience scaling systems to handle high throughput and low latency Strong ability to mentor, elevate peers, and lead cross-team technical initiatives Proven experience driving quality, reliability, and operational excellence at scale ...

ownership Mastery of multiple languages and paradigms; capable of guiding complex trade-offs and technical decisions Extensive experience scaling systems for high throughput and low latency Strong ability to mentor, elevate peers, and lead cross-team technical initiatives Proven experience driving quality, reliability, and operational excellence at scale ...

taste of what you'll be doing Design, build, and maintain the highly reliable Model Serving Layer (Gateways, load balancing, caching, throttling) for low-latency access to LLMs and other generative models. Engineer and maintain production-ready Vector Database and Retrieval-Augmented Generation (RAG) infrastructure, including high-throughput … enforced across all model inputs and outputs Build and maintain the centralised logging, monitoring, and observability stack to track crucial GenAI metrics (hallucination rate, latency, token usage, and drift detection). Ensure the platform and RAG data handling adheres to strict compliance and data privacy regulations (e.g., GDPR) through ...

C#/.NET software (operator tools + backend services) Develop control software integrating hardware subsystems (automation, sensors, motion) Focus on performance and reliability (multithreading, low latency) Integrate with industrial systems via EtherCAT/OPC UA/Modbus (or similar) Support testing, commissioning/deployment, and write key technical ...

Administer Solace appliances/brokers (on-prem & cloud) Production support, incident response, root cause analysis System monitoring, capacity planning, performance tuning WAN optimization for low-latency messaging Automation and documentation ...

Proprietary HFT Location : Cambridge Compensation : Up to £300,000 Company : A proprietary trading firm in Cambridge, specialising in the research and development of ultra-low-latency automated trading strategies, are looking for a Quantitative Researcher with a demonstrable background of iterating rapidly on complex mathematical experiments. ...

Proprietary HFT Location : Cambridge Compensation : Up to £350,000 Company : A proprietary trading firm in Cambridge, specialising in the research and development of ultra-low-latency automated trading strategies, are looking for a Quantitative Researcher with a demonstrable background of iterating rapidly on complex mathematical experiments. ...

What you'll do Architect the full platform stack (Python, TypeScript, Golang) handling trading engine, pricing models, hedging mechanisms and marketplace functionality. Build scalable, low-latency systems for real-time order matching, risk management and market data distribution. Design resilient infrastructure that can handle massive compute trading volumes ...

full software development lifecycle , from concept to delivery Collaborate with policing and government clients to define and deliver solutions Develop and maintain high-volume, low-latency applications ensuring strong performance Test and debug software to ensure reliability and maintainability Support and enhance existing applications and systems Research ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...