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
You will...
- Lead the strategy and execution of perception and prediction evaluation systems.
- Design, code, and test tools, pipelines, services and platforms that support Waabi’s perception and prediction evaluation.
- Collaborate with other teams at Waabi, including research scientists, ML and software engineers, system engineers and program managers to understand their uses and deliver features that improve our overall evaluation ecosystem.
- Participate in the growth and planning for how our evaluation platform scales over the next years.
- Assist in roadmap planning, prioritization, and delivery.
Qualifications:
- 5+ years of industry experience reading and developing production quality software.
- Experience using languages such as Python, Go, or Rust.
- Bachelors degree with a Computer Science, Robotics and/or similar technical field(s) of study.
- Experience working in a team environment on a common codebase.
- Ability to learn new technologies quickly particularly in data analysis.
- Open-minded and collaborative team player with willingness to help others.
- Passionate about self-driving technologies, solving hard problems, and creating innovative solutions.
Bonus/nice to have:
- Experience working with robotics / AV data.
- Experience with perception and prediction metrics (precision, recall, ADE, CTE, etc.).
- Experience with AWS (S3, ECS, Batch, etc.).
- Familiarity with workflow management technology (ex. Airflow).
- Familiarity with advanced statistical analysis.
- Familiarity with large-scale data processing and distributed systems.
- Familiarity with machine learning concepts and evaluation methods
- Comfortable with Linux.
The US yearly salary range for this role is: $155,000 - $213,000 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.
