Impress employers and recruiters.
Choose from hundreds of resume examples.

Impress employers and recruiters.
Choose from hundreds of resume examples.
Tailor your resume to this Lead AI Infrastructure Engineer role.
Rezi rewrites your resume against Avride's job description. Free.

Tailor your resume to this Lead AI Infrastructure Engineer role.
Rezi rewrites your resume against Avride's job description. Free.
Don't guess if your resume is good enough.
See how it scores against the Lead AI Infrastructure Engineer posting at Avride — free, in seconds.

Don't guess if your resume is good enough.
See how it scores against the Lead AI Infrastructure Engineer posting at Avride — free, in seconds.
About the Role
We are seeking a software engineer with a leadership mindset and deep ML infrastructure experience to influence the ML infrastructure layer across the company. The primary challenge is optimizing GPU inference effectiveness for both real-time onboard applications and high-throughput offboard cases.
Responsibilities
- Take on the GPU inference framework, focusing on performance.
- Assume responsibility and ownership for broader ML infrastructure across ML pipelines.
- Collaborate closely with the applied ML team responsible for defining neural model architecture.
Requirements
- 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).
- Authorized to work in the U.S.
- No relocation sponsorship offered.
- Remote work options are not available.
Skills
- PyTorch
- GPU inference
- ML infrastructure
- Distributed systems
- C++
- Multi-threaded programming
Location
- U.S.
Work Type
- Onsite
- Full-time
Experience Level
- 5+ years of experience
About the Company
- Our team is at the core of Avride's self-driving stack.
- We build the base infrastructure layer that powers all autopilot code.
- This 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.
Equal Opportunity
- 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.