# Lead AI Infrastructure Engineer at Avride

> United States · Staff · DevOps / SRE / Infra · open. Source: https://alderhq.app/jobs/greenhouse%3Aavride%3A4423943009 (read 2026-11-14).

## Facts (observed)

- Company: [Avride](https://alderhq.app/companies/avride)
- Location text: Austin, Texas; Austin, Texas
- Where it can be done from (inferred): United States (evidence: "Location: Austin, Texas; Austin, Texas")
- Posted: 2026-09-29 (46 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-12
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://job-boards.greenhouse.io/avride/jobs/4423943009
- Skills listed (inferred): C++, PyTorch, Distributed systems

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (Austin, n 5): p25 $188k, median $201k, p75 $223k
- H-1B filings at this company for similar roles, FY26: 19, median offered wage $140k ([US DOL OFLC LCA disclosure data](https://www.dol.gov/agencies/eta/foreign-labor/performance))

## Description (the employer's text)

### 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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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Aavride%3A4423943009 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.