Senior / Staff Machine Learning Infra Engineer, Waabi

$158-269k

+ equity incentive awards and an annual performance bonus

AWS

Docker

Kubernetes

Python

Linux

Terraform

C++

Rust

Kubeflow

Senior and Expert level

San Francisco Bay Area

Toronto

Remote from Canada, US

AI powered self-driving technology

Job no longer available

AI powered self-driving technology

101-200 employees

B2BTravelCarsAugmented RealitySaaS

Job no longer available

$158-269k

+ equity incentive awards and an annual performance bonus

AWS

Docker

Kubernetes

Python

Linux

Terraform

C++

Rust

Kubeflow

Senior and Expert level

San Francisco Bay Area

Toronto

Remote from Canada, US

101-200 employees

B2BTravelCarsAugmented RealitySaaS

Company mission

To bring commercially viable self-driving technology to society.

Job

Company

Role

Who you are

BS, MS/PhD in Computer Science or similar technical field of study or equivalent practical experience
5+ years of relevant industry experience
Experience in reading and developing production quality software
Deep understanding of Cloud compute and data storage for distributed training and inference workloads
Familiarity with Python, GO, Rust or C++ ecosystems
Experience working with public cloud platforms (AWS preferred)
Experience with infrastructure as code systems (Terraform preferred)
Experience in job scheduling and resource allocation
Experience with containers and container orchestration (i.e., Docker, ECS, Kubernetes)
Experience and high level of comfort working with Linux systems
Experience with building platform services that enable other teams to do their best work
Open-minded and collaborative team player with the willingness to help others
Passionate about self-driving technologies, solving hard problems, and creating innovative solutions
Experience working in an Agile/Scrum environment

Desirable

Experience with on-premise servers, network equipment and scale-out storage systems
Experience with CI/CD pipelines and release management
Experience in common ML tools, workflows and frameworks (i.e. systems like Kubeflow or MLFlow)
Understand system performance tuning at software, hardware, and network levels
Have good understanding of GPUs and accelerators in ML training and inference use cases

What the job involves

Work alongside a team of multidisciplinary Engineers and Research Scientists using an AI-first approach to enable safe self-driving at scale
Collaborate with cross-functional teams in the company to understand the growing need and pain points in cloud usage
Propose cloud strategies around compute and data usages for training and simulation workloads
Design and implement scalable and resilient cloud infrastructure optimized for long term reliability and adaptability
Devise and promote best practices for cloud usages in training and simulation environments, oversee cloud strategies and usages across the whole company

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 at Welcome to the Jungle

Insights

Led by a woman

Top investors

81% employee growth in 12 months

Glassdoor (4.2)

Company

Funding (2 rounds)

Jun 2024

$200m

SERIES B

Jun 2021

$73.2m

SERIES A

Total funding: $273.2m

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

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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