Posting record
Open 12+ days
- Avride's site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Avride, so its true age is longer.
Last checked Nov 3, 2026.
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Upload your resumeWhat it asks of you
- 5+ years of experience
What the posting discloses
Not stated: Pay, real vacancy, AI screening.
Why these three
Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.
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Skills mentioned
About the role
About the Team
Our team is at the core of Avride's self-driving stack. We build the base infrastructure layer that powers all autopilot code. It includes a C++ framework for implementing autonomy components, execution graph building and optimization systems, as well as runtimes that execute those graphs, both onboard and in simulation.
The vast part of the execution graph is implemented as a chain of neural network operations. The onboard mode relies on stable latencies of the inference of those networks, while in simulation we also optimize throughput at scale.
About the role
We’re looking for a software engineer with a leadership mindset and deep ML infrastructure experience. You will decide and influence the ML infrastructure layer across the company. The biggest challenge we’re facing at the moment is the effectiveness of GPU inference - both for onboard applications with near real-time guarantees and for offboard cases that target high throughput and deterministic execution. It is the first priority within this role.
What you'll do
- At first, you will take on the GPU inference framework, focusing on performance
- Later, the role assumes responsibility and ownership for broader ML infrastructure scattered across ML pipelines
- Close collaboration with the applied ML team responsible for defining the neural model's architecture
What you'll need
- Experience with PyTorch
- Understanding of how GPUs work
- Experience in diagnosing and resolving performance issues
- Strong record of building infrastructure including distributed systems
- 5+ years of experience with C++
- Programming experience in multi-threaded environments - multiple processes, threads, timers, and interrupts
#LI-MS1
Candidates are required to be authorized to work in the U.S. The employer is not offering relocation, sponsorship, and remote work options are not available.
Avride is an equal opportunity employer and committed to providing reasonable accommodations to qualified applicants and employees with disabilities to ensure they have equal access to employment opportunities. Avride complies with the Americans with Disabilities Act (ADA), if you need a reasonable accommodation to assist with the application or hiring process, or to perform the essential functions of a job, please email jobs@avride.ai .
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