Gravis Robotics Industry · Engineering Internship

Working Student — Fleet Observability & Data Visualization

CHF 25'000 – 45'000 / year
ZÜRICH LLMAI-NATIVE

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

What we offer

  • 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

Qualifications

  • 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

Bonus Skills

  • 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
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