Lead AI Infrastructure Engineer

Avride
Austin, TX

Who this role is best for

Geared toward experienced engineers comfortable with GPU inference optimization and C++ infrastructure development, working in a team focused on self-driving technology in Austin, Texas.

Best fit for

  • Experienced C++ engineers with a track record in distributed system design and performance tuning
    — “Strong record of building infrastructure including distributed systems”
  • Individuals with a background in autonomous systems or simulation environments
    — “execution graph building and optimization systems, as well as runtimes that execute those graphs, both onboard and in simulation”

Things to consider

  • No remote work options available, requiring in-person presence in Austin, Texas
    — “remote work options are not available”
  • Candidates must be authorized to work in the U.S., excluding those needing visa sponsorship
    — “Candidates are required to be authorized to work in the U.S. The employer is not offering relocation, sponsorship”

How to stand out

  • Highlight hands-on GPU performance optimization and real-time inference work in your resume and interview
    — “the biggest challenge we’re facing at the moment is the effectiveness of GPU inference”
  • Emphasize your experience in multi-threaded environments and low-latency system design
    — “Programming experience in multi-threaded environments - multiple processes, threads, timers, and interrupts”
  • Showcase leadership experience in infrastructure decisions or cross-team collaboration
    — “You will decide and influence the ML infrastructure layer across the company”
  • Demonstrate a history of working with PyTorch and neural network execution frameworks
    — “Experience with PyTorch”
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • improve GPU inference performance
  • build and optimize ML infrastructure
Typical background
software engineeringML infrastructure

Skills & requirements

Required

C++PyTorchGPU Performance OptimizationDistributed SystemsMulti-threaded Environments

Preferred

Diagnosing And Resolving Performance IssuesExperience With ML Infrastructure

Stack & domain

PyTorchC++Multi-threaded EnvironmentsLeadership MindsetDeep ML Infrastructure ExperienceAISelf-driving StackNeural Network Operations

About the role

Original posting from Avride via Greenhouse

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.

Source: Avride careers (Greenhouse)

Similar roles