Algorithm Applied Researcher

About the job Oriient is solving indoor positioning by turning the Earth's magnetic field into a digital map. We utilize the unique magnetic signatures of buildings, combined with phone-based IMU and magnetometer data. We are looking for an engineer to help us blend classical estimation with learned motion models to achieve meter-level accuracy.

What you’ll work on

Hybrid Algorithm Development: Developing and refining the localization engine using a mix of classic estimation methods and Deep Learning.

Signal Analysis: Analyzing and processing signals from the IMU, magnetometer, and barometer to account for real-world noise.

Full-Cycle Research: Reading academic papers to find new ways to improve convergence and then watching your changes improve accuracy across thousands of buildings.

What we’re looking for

B.Sc. in EE, Applied Math, or a related field.

3+ years of experience in signal processing, estimation, or sensor fusion.

Experience with Deep Learning for time-series or movement estimation.

Proficient Python; you care about correctness and seeing your work deployed in large-scale retail and healthcare environments.

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