DeepRec.ai

Flight Test / Data Engineer – Acoustic Systems

Stellenbeschreibung:

Overview

About the role. We are supporting a Munich-based deep-tech company building distributed acoustic sensing systems. Their technology needs to be tested in real-world environments, including field trials, drone tests and controlled chamber testing. They are looking for a Flight Test / Data Engineer who can take ownership of the data side of these tests. This person does not need to come from a flight test background; the most important skill is being able to work with real-world sensor data, process it properly, structure it, score it and identify errors in the data pipeline.

Responsibilities

  • Support acoustic data collection from field tests, drone tests and chamber testing.
  • Work with drone operators and interns to conduct structured test campaigns.
  • Record, process and organise test data.
  • Perform post-processing and quality checks on acoustic sensor data.
  • Score and structure results in databases.
  • Identify, debug and document errors in the data collection and processing flow.
  • Help improve how test data is captured, labelled, stored and used by engineering teams.
  • Work closely with ML, embedded and hardware engineers to make test data usable.

What they’re looking for

  • Strong data engineering or data processing experience.
  • Comfortable working with messy, real-world sensor data.
  • Experience with databases and structured data workflows.
  • Strong Python or similar scripting skills.
  • Ability to debug errors across data collection, storage and processing.
  • Practical mindset; happy to be close to real-world testing rather than only working behind a desk.
  • Interest in learning flight testing and drone-based data collection on the job.

Nice to have

  • Experience with acoustic data or signal processing.
  • Experience with drone testing, robotics testing or field testing.
  • Experience in defence, aerospace, robotics, autonomous systems or industrial sensing.
  • Experience supporting ML teams with high-quality labelled/structured data.

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Stelleninformationen

  • Veröffentlichungsdatum:

    30 Jul 2026
  • Standort:

    München
  • Typ:

    Vollzeit
  • Arbeitsmodell:

    Vor Ort
  • Kategorie:

  • Erfahrung:

    2+ years
  • Arbeitsverhältnis:

    Angestellt

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