Data Engineer, Autonomous Systems, at Ellison Institute of Technology (EIT) in Oxford, United Kingdom. The Scientific Compute and Data team builds the compute, data, and tooling foundation behind EIT's science, operating cloud and GPU infrastructure, data platforms, and shared data models that enable labs to accelerate experiments. You will join the AutoLabs project, enabling the data pipeline that captures, stores, and serves high-frequency multimodal data from edge devices to the cloud. The role spans an edge-to-cloud telemetry stack (MQTT, Kafka, media streams such as HLS), streaming APIs, and hardware integrations across robotic systems, sensor rigs, and lab instruments. Our labs generate raw data for models in vision-language-action, orchestration and monitoring, and world models used to simulate experiments before execution. As a Data Engineer, you will work alongside AI researchers, software engineers, robotics engineers, and domain scientists to build the data layer that makes autonomous operations possible. You will contribute to an engineering culture that emphasizes robust design, testing, and collaboration while supporting rapid prototyping and responsiveness to changing landscapes.

Day-to-day you might: Build high-throughput, low-latency ingestion for live video, sensor telemetry, robot joint state, and instrument control signals, validating data at the edge before it reaches the cloud. Work across the edge-to-cloud stack—from edge devices and MQTT brokers to Kafka topics, cloud storage, and APIs that serve scientists and ML pipelines. Transform streams of rob

Data Engineer, Autonomous Systems, at Ellison Institute of Technology (EIT) in Oxford, United Kingdom. The Scientific Compute and Data team builds the compute, data, and tooling foundation behind EIT's science, operating cloud and GPU infrastructure, data platforms, and shared data models that enable labs to accelerate experiments. You will join the AutoLabs project, enabling the data pipeline that captures, stores, and serves high-frequency multimodal data from edge devices to the cloud. The role spans an edge-to-cloud telemetry stack (MQTT, Kafka, media streams such as HLS), streaming APIs, and hardware integrations across robotic systems, sensor rigs, and lab instruments. Our labs generate raw data for models in vision-language-action, orchestration and monitoring, and world models used to simulate experiments before execution. As a Data Engineer, you will work alongside AI researchers, software engineers, robotics engineers, and domain scientists to build the data layer that makes autonomous operations possible. You will contribute to an engineering culture that emphasizes robust design, testing, and collaboration while supporting rapid prototyping and responsiveness to changing landscapes.

Day-to-day you might: Build high-throughput, low-latency ingestion for live video, sensor telemetry, robot joint state, and instrument control signals, validating data at the edge before it reaches the cloud. Work across the edge-to-cloud stack—from edge devices and MQTT brokers to Kafka topics, cloud storage, and APIs that serve scientists and ML pipelines. Transform streams of rob