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.
You will…- 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. You have a thorough understanding of the fundamentals of signal processing, both classical (filtering, estimation) and learning-based (image denoising and super-resolution, 2D and 3D segmentation). You know how to apply insights from the underlying mathematics (Toeplitz matrices, spectral bandwidth, M-estimators) to design robust numerical algorithms that operate on data from real-world sensors.
- Real-time and Embedded Systems You have 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. You are comfortable rapidly building proofs of concept in a high level language like Python, Julia, or MATLAB. You are equally comfortable reading and developing production-quality software.
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.
- 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!
Skills Required
- Thorough understanding of classical and learning-based signal processing, including filtering, estimation, image denoising, super-resolution, and 2D/3D segmentation
- Ability to apply mathematical signal-processing concepts to design robust numerical algorithms for real-world sensor data
- Experience with high-throughput data inputs and latency-sensitive algorithms under limited compute and memory constraints
- Ability to rapidly prototype in Python, Julia, or MATLAB
- Ability to read and develop production-quality software
- Industry experience in 1D, 2D, 3D, or 4D signal processing
- Experience with numerical algorithms and mathematical optimization, including BLAS, CHOLMOD, Gauss-Newton, L-BFGS, or linear programming
- Experience with real-time methods such as causal and recursive filters, recurrent neural networks, or transformers
- Experience with systems programming, including buffer management, asynchronous communication, or hardware accelerators
- Knowledge of performance profiling and optimization
What We Do
Waabi, founded by AI pioneer and visionary Raquel Urtasun, is an AI company building the next generation of self-driving technology. With a world class team and an innovative approach that unleashes the power of AI to “drive” safely in the real world, Waabi is bringing the promise of self-driving closer to commercialization than ever before. Waabi is backed by best-in-class investors across the technology, logistics and the Canadian innovation ecosystem, including Khosla Ventures, Uber, 8VC, Radical Ventures, OMERS Ventures and BDC Capital’s Women in Technology Venture Fund. To learn more visit: waabi.ai Press: [email protected] Business: [email protected]
