Job Description

About Us

STARK is a new kind of defence technology company revolutionising the way autonomous systems are deployed across multiple domains. We design, develop, and manufacture high-performance unmanned systems that are software-defined, mass-scalable, and cost effective. This provides our operators with a decisive edge in highly contested environments.

We are focused on delivering deployable, high-performance systems, not future promises. In a time of rising threats, STARK is bolstering the technological edge of NATO Allies and their Partners to deter aggression and defend Europe today.

Responsibilities

• Field Log Analysis: review flight logs immediately after flight tests to verify data quality and sensor health.
• Physics & Weather Correlation: match log anomalies with physical reality. If the drone dropped 2 meters, identify if it was a barometer error, a motor desync, or a downdraft.
• Data Labeling: annotate specific flight segments (e.g., "automatic landing," "EW jamming test," "high-G turn") so analysts know exactly what happened in each timeframe.
• Data Cleaning: filter out noise, correct timestamp alignments between different sensors, and remove invalid data points before the data enters our main pipeline.
• Pipeline Maintenance: write and maintain Python scripts that automate the initial ingest and validation of field data.
• Feedback Loop: report critical failures to the engineering team immediately while still in the field to enable requisition of the data.

Qualifications

• Experience analyzing flight logs (PX4, ArduPilot, or proprietary stacks).
• Strong understanding of UAV aerodynamics and control theory (PID loops, EKF).
• Proficiency in Python (pandas, NumPy, matplotlib) for data processing.
• Ability to work in field conditions (outdoors, laptop-based, variable weather).
• Knowledge of sensor physics (IMU, GNSS, magnetometers, pitot tubes).

Nice-to-Have:

• Experience with flight visualization tools (FlightPlot, PlotJuggler).
• Background in experimental physics or mechanical engineering.
• Experience with SQL or time-series databases.