小鹏汽车GPU tools高级/资深/专家工程师

1. Architect and implement agentic workflows that plan, reason, call tools/APIs, and coordinate with humans or other agents. 2. Select, extend, or build frameworks (e.g., LangChain, AutoGen, CrewAI, MetaGPT, LangGraph) to accelerate delivery while avoiding vendor lock-in. 3. Own the MLOps lifecycle: data collection, evaluation harnesses, safety filters, CI/CD, and observability for deployed agents. 4. Integrate enterprise systems & data sources (REST/GraphQL, Kafka, vector databases, Kubernetes) so agents can act on real business objects. 5. Mentor and review code for junior engineers; drive best practices in prompt engineering, evaluation, and secure coding. 6. Research emerging techniques (toolformer, self-reflection, role specialization) and translate findings into the product roadmap.

• Lead the software development in C/C++, Python, and in GPU languages such as CUDA, ROCm, or Triton• Analyze metrics and identify opportunities based on offline and online testing, develop and deliver robust and scalable solutions.• Work with cutting-edge hardware stacks and a fast-moving software stack to deliver best-of-class inference and optimal cost.• Engage with key partners to understand and implement inference and training optimization for state-of-the-art LLMs and other models.

• Architect Performance Tooling: Develop infrastructure tools/libraries for GPU performance analysis, visualization, and automated workflows used across GPU SW/HW development life cycle.   • Unlock Architectural Insights: Analyze GPU workloads to identify bottlenecks and define new hardware profiling features that enhance perf debug and profiling capabilities.  • AI-Powered Automation: Build AI/ML-driven tools to automate performance analysis, generate perf optimization guidance, and improve user experience of profiling infrastructure.  • Cross-Stack Collaboration: Partner with kernel developers, system software teams, and hardware architects to support performance study, improve CUDA software stack, and co-design performance-centric solutions for current and next-generation GPU architecture

We are now looking for a software engineer intern. The NVIDIA Developer Tools team is seeking a software engineer intern to join our effort to advance the state of graphics and compute performance analysis and tuning. You will help developers of groundbreaking products in Automotive, VR, Gaming, Deep Learning and High Performance Computing to analyze and improve the performance of their products. You will have the opportunity to learn the pipeline and driver stack of the world's most sophisticated GPUs, work with a group of talented engineers from all over the world, and apply your software development skills to improve our products. What you’ll be doing: • Develop algorithms to exercise various parts of the GPU pipeline to verify our performance metrics. • Deeply dive into NVIDIA GPU architecture and software stack, develop new feature for NVIDIA GPU performance profiling tools. • Write unit and integration tests to verify the functionality, performance, stability, resource usage of our products.