[Hiring] Research Engineer, Sensor Signal Processing @Waabi

Role Description

As a Research Engineer in Sensor Signal Processing, you will be a key contributor to the research and development of Waabi’s signal processing stack for autonomous driving. You will collaborate with our team of world-renowned scientists and engineers to build innovative, practical, and scalable solutions that handle massive amounts of sensor data (camera, LiDAR, radar, and other modalities) with low latency and high reliability. We value original, high-impact ideas and rigorous experimental validation.

• Be part of a multidisciplinary team of scientists and engineers working on a system that turns raw sensor data captured under diverse environments into useful signals for autonomous driving.
• Design and implement novel signal processing techniques for sensor data acquisition, fusion, and filtering.
• Optimize signal processing algorithms for deployment on parallel computing architectures (e.g., CPU, GPU, DSP, and specialized accelerators).
• Collaborate with Waabi’s autonomy and hardware teams to ensure the robustness of the entire system.
• Have the opportunity to make contributions to high-impact research papers submitted to top conferences or journals (e.g., TSP, TIP, ICRA, IROS, CVPR, NeurIPS, SIGGRAPH, HPG).

Qualifications

• Signal Processing Theory and Practice: Thorough understanding of the fundamentals of signal processing, both classical (filtering, estimation) and learning-based (image denoising and super-resolution, 2D and 3D segmentation).
• Real-time and Embedded Systems: Experience working with high-throughput data inputs in latency-sensitive algorithms, all under a limited compute and memory budget.
• Rapid Prototyping and Shipping Production Software: Comfortable rapidly building proofs of concept in a high-level language like Python, Julia, or MATLAB; equally comfortable reading and developing production-quality software.

Requirements

• Bonus: Industry experience in 1D (audio), 2D (image), 3D (point cloud), or 4D (radar) signal processing.
• Experience with numerical algorithms and mathematical optimization: BLAS, CHOLMOD, Gauss-Newton, L-BFGS, linear programming.
• Experience with real-time methods: causal and recursive filters, recurrent neural networks, transformers.
• Experience with systems programming: buffer management, asynchronous communication, hardware accelerators.
• Solid knowledge in performance profiling and optimization.

Benefits

• Competitive compensation and equity awards.
• Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).
• Unlimited Vacation.
• Flexible hours and Work from Home support.
• Daily drinks, snacks and catered meals (when in office).
• Regularly scheduled team building activities and social events both on-site, off-site & virtually.
• As we grow, this list continues to evolve!