Senior Software Engineer, Waabi
Simulation Agents and Scenarios
$122-215k
+ Equity + Annual performance bonus
AI powered self-driving technology
Open for applications
AI powered self-driving technology
101-200 employees
Open for applications
$122-215k
+ Equity + Annual performance bonus
101-200 employees
Company mission
To bring commercially viable self-driving technology to society.
Role
Who you are
- Bachelor's in computer science, engineering, machine learning, or a related technical discipline
- Demonstrated software engineering excellence through previous internships, work experience, coding competitions, and/or research projects and papers
- Strong quantitative background, familiarity with machine learning and deep learning
- Open-minded and collaborative team player with the willingness to help others
- Passionate about self-driving technologies, solving hard problems, and creating innovative solutions
Desirable
- Master/PhD in machine learning, computer science, engineering, or a related field
- Experience in self-driving or related fields
- Experience with simulation for self-driving or related fields
- Experience with training and deploying deep learning models
- Familiarity with one or more of the following fields: traffic simulation, imitation learning, reinforcement learning, planning, and/or robotics
- Experience in TensorFlow or PyTorch
What the job involves
- As a Software Engineer on our Behaviors team, you will create the next generation of simulation software for autonomous driving
- You will work closely with our multidisciplinary team of world-renowned scientists and software engineers to build innovative, practical, and scalable solutions to challenging problems as part of our next-generation self-driving solution
- Work with research scientists and engineers across Waabi to develop and maintain a portfolio of algorithms, models, and tools that power Waabi World’s scenario framework
- Collaborate with users to create scenarios for training and testing the Waabi Driver at scale
- Deliver new capabilities that extend the realism and diversity of scenarios we can simulate
- Productionize research prototypes into reliable and scalable products in Waabi World
- Design and implement tools to accelerate our ML development lifecycle, including our training and evaluation infrastructure
- Champion engineering excellence, ensuring high-quality, well-structured and tested code
- Participate in roadmap ideation, planning, and prioritization
Our take
Autonomous vehicle technology is rapidly developing and many sectors are recognising its value. However, whilst the self-driving industry has made significant advancements there is much more that can be done. There are challenges in this space surrounding scale and developing commercially viable self-driving technology.
Waabi hopes to tackle these challenges and be the leader in self-driving technology with their "AI first approach". The company said that combined with a closed-loop simulator, this approach will allow both common driving scenarios and safety-critical edge cases to be tested at scale - solving one of the key issues in the industry.
Waabi successfully raised one of the largest Series A rounds ever raised in Canada, and has gone on to raise fresh Volvo and Uber-led funding in early 2024. While the company's focus is currently on autonomous long-haul trucking (launching its first generation of trucks in November 2022), the company is well set to lead the next generation of self-driving technology.
Kirsty
Company Specialist
Insights
Company
Funding (2 rounds)
Jun 2024
$200m
SERIES B
Jun 2021
$73.7m
SERIES A
Total funding: $273.7m
Company benefits
- Equity awards
- Medical, Dental and Vision coverage (for full-time employees only)
- Unlimited Vacation
- Flexible hours and Work from Home support
- Regularly scheduled team building activities and social events both on-site, off-site & virtually
- Annual performance bonus
Company HQ
Downtown Toronto, Toronto, ON
Articles
Leadership
Raquel Urtasun
(CEO)Previously worked at Uber as Chief Scientist, Head of Uber ATG R&D. Is also a professor at the University of Toronto.
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