Machine Learning Research Engineer at RBC Borealis applying ML technology to complex problems with a focus on generative AI, NLP, and time series analysis.
About the role
- Research Engineer focusing on signal processing for autonomous vehicles at Waabi. Collaborating with scientists and engineers to innovate and optimize systems for sensor data.
Responsibilities
- 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).
Requirements
- 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.
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!
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