Research Engineer, Sensor Signal Processing
Job Summary
As a Research Engineer in Sensor Signal Processing you will be a key contributor to the research and development of Waabis 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 Waabis 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 SystemsYou 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.
Required Experience:
IC