Avride Benefits Overview

Design, build, and operate Python backend services, APIs, databases, and labeling pipelines for massive autonomous vehicle sensor datasets. Own systems from ingestion through delivery, integrate vendors and internal tools, develop validation and quality monitoring, improve human labeling with ML automation, and collaborate with ML and perception teams. Lead technical design, review code, mentor engineers, and support production reliability through deployment, monitoring, and on-call responsibilities.

Lead development of Avride’s ML infrastructure, initially owning GPU inference performance for onboard and simulation workloads. Build and optimize C++ execution frameworks, runtimes, and distributed infrastructure supporting neural network pipelines. Collaborate with applied ML teams on model architecture, diagnose performance issues, and expand ownership across broader ML pipelines. The role requires deep GPU and PyTorch knowledge, distributed systems experience, and strong expertise in multithreaded C++ environments.

The QA Engineer will design and execute testing plans for autonomous driving software, analyze test scenarios, and document outcomes. Collaboration with cross-functional teams is crucial for improving test processes and safety metrics.