Localization Algorithm Engineer

Job Description

Description:
This role focuses on developing and optimizing localization algorithms using probabilistic methods and multi-sensor fusion to improve positioning accuracy. You will prototype, simulate, and refine solutions into production-ready code while collaborating across software, hardware, and systems teams in a fast-paced R&D environment.
Responsibilities/skills:
• Develop and refine PC-based localization algorithms using particle filters and other probabilistic techniques.
• Implement sensor fusion strategies that integrate data from IMUs, wireless signals, and other external sources to enhance position accuracy.
• Design simulations to test and validate your algorithms under diverse real-world conditions (e.g., multipath, noise, varying environments).
• Leverage Python, C++, C#, or MATLAB to prototype and optimize algorithms before porting them to production software.
• Conduct thorough performance evaluations of localization algorithms, identifying bottlenecks and implementing data-driven optimizations.
• Collaborate with embedded, FPGA, and RF teams to improve the performance of the location tracking system.
• Stay current with the latest academic and industry research in probabilistic localization, sensor fusion, and state estimation.
• Rapidly prototype novel concepts, iterating on algorithm design to reach production-level stability and robustness.
• Work cross-functionally with software, hardware, and systems engineers to integrate localization algorithms into larger systems.
• Contribute to code reviews, knowledge sharing, and team brainstorming sessions to maintain a high level of technical excellence.

Qualifications:
• Solid background in state estimation, probability theory, and advanced filtering techniques (particle filters, Kalman filters, etc.).
• Proficiency in at least one programming language (Python, C#, C++, MATLAB) used for developing and evaluating algorithms in a PC-based environment.
• Solid understanding of DSP algorithms and IQ radio processing.
• Experience translating theoretical models into efficient, production-ready code, with an emphasis on real-time or near-real-time performance.
• Familiarity with sensor data processing (IMU, etc.) and a keen interest in multi-sensor fusion methods.
• Adept at using data analytics and simulations to diagnose issues, validate assumptions, and refine algorithmic approaches.
• Passionate about exploring new ideas, adapting cutting-edge research, and creatively applying them to solve challenging localization problems.
• Enjoys working as part of a multi-disciplinary R&D team, bridging gaps between software, hardware, and system-level designs.
• Thrives on tackling open-ended challenges, taking ownership of tasks, and seeking continuous learning opportunities.