Senior / Staff Perception Engineer

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 Senior Perception Engineer, you will be at the forefront of advancing and deploying perception algorithms for our self-driving vehicles. You will work closely with our team of world-renowned scientists and engineers specializing in deep learning, computer vision, and self-driving technologies to develop cutting-edge solutions that enable our vehicles to perceive the world around them. We value originality, innovation, and a commitment to rigorous experimental validation and code quality as we strive to bring research ideas into production and push the boundaries of self-driving technology. You will... - Prototype, evaluate, and iterate on perception algorithms, using real-world data and simulations, to improve the accuracy, robustness, and safety of our self-driving technology. This includes working on 3D detection and tracking of traffic agents as well as semantic understanding of various traffic scenes. - Formulate problems and propose pragmatic and long-term solutions based on research insights, leveraging your expertise in deep learning, computer vision, and self-driving. - Support productizing and deploying perception algorithms to our self-driving vehicles, collaborating closely with platform teams to ensure seamless integration of research findings into our self-driving system. - Champion engineering excellence, ensuring high-quality, well structured and tested code. - Collaborate in a multidisciplinary team solving problems related to perception, motion forecasting, planning, traffic modeling and sensor simulation, integrating research findings into our self-driving system and contributing to the development of a unified self-driving platform. - Stay up-to-date with the latest advancements in the field of artificial intelligence, machine learning, computer vision, and self-driving technologies, and apply insights from the literature. - Work with large datasets from various sources as well as Waabi World, our high-fidelity simulator. - Contribute to the publication of research findings in conferences as well as Waabi's blog. Qualifications: - MS/PhD or Bachelors degree with a minimum of 4 years of industry experience in Computer Science, Machine Learning and/or similar technical field(s) of study. - Experience working on applied research projects and shipping machine learning features/models into production. - Experience driving projects on 3D detection, tracking of traffic agents and/or semantic understanding of various traffic scenes. - Passion for taking research ideas and turning them into practical solutions for real-world applications. - Solid understanding of computing fundamentals, including code efficiency. - Proficient in Python programming with a focus on writing high-quality, well-structured, and tested code. - Comfortable working with large datasets for machine learning applications. - Strong grasp of machine learning and computer vision literature, including current trends and state-of-the-art techniques. - Open-minded and collaborative team player with the willingness to help others. - Experience and excitement in supporting a fast-paced high-growth environment. - Passionate about being part of an organization solving self-driving technologies. Bonus/nice to have: - Previous experience in multimodal sensor fusion. - Previous experience in self-driving technology or related fields. - Publications in top-tier conferences or journals related to computer vision, machine learning, or robotics. - Experience in working with platform teams and collaborating with research teams to implement and validate deep learning models. - Proficiency in Pytorch, Rust, C++ and/or CUDA. The US yearly salary range for this role is: $158,000 - $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.