Working Student — Fleet Observability & Data Visualization

Your Responsibilities

• Build and maintain pipelines to fetch metrics from machines deployed in the field


• Organize and structure operational data so it can be visualized


• Design and implement live dashboards on our office display to distribute the information company wide


• Set up automated analysis of trends and long-term averages across different metrics


• Develop anomaly-detection workflows to flag decalibration, sensor drift, or unexpected behavior before it becomes an incident


• Leverage AI agents to accelerate data exploration, summarization, and routine analysis tasks

• Hands-on experience with the full data lifecycle of a production robotics fleet — from raw telemetry to actionable insight


• Direct visibility into how a deep-tech startup uses data to scale up its operations


• The opportunity to take ownership of a system that the whole company relies on every day

• EU/EFTA students


• Currently enrolled at a Swiss university (Bachelor's or Master's level), ideally in computer science, data science, electrical engineering, robotics, or a related field


• Proficiency in Linux systems and comfort working from the command line


• Experience with observability and visualization tools such as Grafana, Prometheus, Foxglove, Kibana, Datadog, or comparable stacks


• Working knowledge of modern web technologies (HTML/CSS, JavaScript/TypeScript, and a frontend framework such as React, Vue, or Svelte)


• Working knowledge of git


• Reliable, detail-oriented, and comfortable owning a project end-to-end


• Good communication skills in English

• Experience with time-series databases (Prometheus, InfluxDB, TimescaleDB, VictoriaMetrics, or similar)


• Familiarity with statistical methods for anomaly detection or trend analysis Experience with data pipelines, message brokers, or stream processing (MQTT, Kafka, Zenoh, ROS bags, or similar)


• Familiarity with robotics concepts (sensors, coordinate frames, calibration, etc.)


• Practical experience using AI agents or LLM-based tools in a development or analysis workflow


• Prior experience building dashboards or monitoring systems (ideally in production)


• Long-term engagement preferred, with the possibility to grow your responsibilities over time

Diese Anzeige stammt von ats_lever. Originalanzeige ansehen ↗