Asks for

The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“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.”

Values

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

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.

With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai

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.

The US yearly salary range for this role is: $155,000 - $269,000 USD in addition to competitive perks & benefits. Waabi US Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.

Perks/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!

Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact!

Waabi is an equal opportunity employer. We celebrate diversity and are committed to creating a supportive, inclusive, and accessible workplace for all our employees. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, age, citizenship, religion, sex, sexual orientation, gender identity or expression, military or veteran status, marital status, pregnancy or parental status, caregiver status, disability, or any other characteristic protected by law. We make workplace accommodations for qualified individuals with disabilities as required by applicable law. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.