Senior Software Engineer, Auto Labelling

Job Description

Job Description

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:

You will...

- Be part of a team of multidisciplinary Research Scientists and Engineers working on building a cutting-edge offline perception and auto-labelling system leveraging computer vision, and machine learning.

- Manage the end-to-end orchestration of the large-scale auto-labelling training, evaluation and automation eco-system.

- Architect and scale the pipeline to handle large-scale data and user requests using distributed computing frameworks.

- Collaborate with ML researchers and engineers to seamlessly deploy new architectures into the production environment.

Qualifications:

- Bachelors degree with a Computer Science, Robotics and/or similar technical field(s) of study.

- 3+ years of experience developing solutions in ML systems or the ML software stack.

- Deep understanding of ML system architecture, performance analysis, and profiling tools to optimize complex workloads.

- Experience with the end-to-end productionization of deep learning models, particularly large-scale online inference.

- Proficient in Python with a track record of writing high-quality, well-structured, and well-tested "production-grade" code.

- Open-minded and collaborative team player with the willingness to help others.

 

Bonus/nice to have:

- Familiarity with 3D data (LIDAR/Point Clouds) and multi-modal sensor fusion perception models.

- Experience working with large Vision-Language Models (VLMs)

The US yearly salary range for this role is: $170,000 - $220,000 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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.