Backend Navigation Engineer

About the company QLAN is a technology integrator that implements end-to-end AI solutions into the business processes of large companies and government structures.

What you will be doing:

• Processing data collected during car runs.
• Restoring and correcting the vehicle's movement track.
• Using the Kalman filter for processing navigation data.
• Performing track-to-road network matching (map matching).
• In the case of an extended hardware complex, merging data: CAN; USB GPS; video; navigation sources.
• Developing a data converter into the format specified by the technical specification.
• Verifying the quality and correctness of the received data batches.
• Automating data verification using Python.
• Calculating polygon coverage.
• Participating in calibration runs and analyzing the results.
• Identifying problems in the data and determining their causes.
• Interacting with the sensor integration engineer and the project manager.

Requirements ** Mandatory:** • Proficient Python. • Experience in data processing and analysis. • Understanding of navigation and positioning principles. • Practical experience with the Kalman filter. • Understanding of map matching / road network mapping algorithms. • Ability to work with large data arrays. • Skills in automating data processing and verification. • Ability to independently understand the quality and structure of raw data.

Important: **• Experience with GPS/GNSS, CAN, video and time series, sensor fusion, geodata and GIS, NumPy / Pandas / SciPy. • Experience with automotive or robotics systems. • Experience processing data from multiple sensors. **

We offer:

• Project-based employment with a flexible work format
• Direct communication with technical management without bureaucracy
• Opportunity to grow into a full technical role within the company