NIO Inc.

Build and optimize production-grade AI inference infrastructure for large language and vision-language models across cloud, edge, and hybrid environments. Your work will power intelligent automotive systems through high-performance kernels, model optimization, and scalable serving systems.

Lead deep CPU and virtualization performance analysis for ARM-based systems, using PMU counters, microarchitectural techniques, and Linux tooling to optimize system software and hypervisors. The role focuses on improving throughput, latency, determinism, and virtualization efficiency across NIO’s smart-vehicle technology stack.

Join NIO’s SkyOS team as a Staff System Engineer and Researcher, advancing full-domain vehicle operating systems for smart electric vehicles. The role combines original systems research with hands-on implementation, optimization, and production deployment across the software stack.

Join NIO’s SkyOS team to design and optimize low-level operating system software for intelligent electric vehicles. This role spans kernels, networking, file systems, drivers, hypervisors, and other systems layers from prototype through production.

Build automated validation and test infrastructure for NIO’s next-generation automotive operating system and hypervisor platform. This hands-on role combines embedded software testing, hardware-based validation, CI pipeline development, and functional-safety-focused debugging.

Lead the development of foundational low-level software for NIO’s next-generation ECU simulation platform, enabling high-throughput virtualization and validation for software-defined vehicles. This high-impact role spans hypervisors, hardware architecture, Linux drivers, and automotive real-time systems.

Conduct a three-month research internship proving the safety of concurrent kernel primitives using formal methods, bounded model checking, and low-level hardware analysis. The role combines C systems programming, weak-memory concurrency, and AI-assisted formal verification.

AI Research Engineer developing and deploying advanced AI systems that automate enterprise workflows and improve decision-making. The role bridges applied research and production engineering across foundation models, intelligent assistants, and autonomous workflows.