SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Oriient has developed hardware-free indoor GPS technology using Earth's magnetic field and AI to provide hyper-accurate positioning in environments where traditional GPS fails—malls, hospitals, transit hubs, and other indoor spaces. As an Algorithm Engineer on the core algorithm team, you will research, design, and deploy classical and machine-learning-based localization modules that work in complex, real-world environments.
You will own the full cycle from theoretical research and academic papers through prototyping, validation, and production deployment at scale. Your work will involve geomagnetic positioning, IMU sensor fusion, signal processing, and deep learning to overcome the physical limitations of indoor navigation. You'll develop evaluation pipelines and infrastructure to test new features against massive real-world datasets, and collaborate with a flat, high-powered R&D team where individual contributions are visible and vital.
The company is VC-backed and in hyper-growth, deploying technology across retail giants, smart buildings, and large healthcare campuses globally.
REQUIREMENTS:
- B.Sc. in Electrical Engineering from a top-tier university (GPA 85+); M.Sc. is a plus
- 3+ years of hands-on experience in algorithm design, specifically in Signal Processing, Kalman/Particle Filters, or Deep Learning
- High proficiency in Python and MATLAB
- Ability to read and translate academic papers into working simulations
- Data-driven mindset; comfort digging into large datasets to understand anomalies and edge cases
- Background in cloud platforms or software engineering is a plus
