英伟达Deep Learning Senior Engineer, End-To-End Autonomous Driving
任职要求
At NVIDIA, we are seeking exceptional engineers to join our autonomous driving team to design, implement, and deploy cutting-edge end-to-end autonomous driving systems, running on NVIDIA chips in mass-production vehicles. Our strategy has evolved from AI 1.0 — building a driver from scratch — to AI 2.0 — teaching an intelligent agent to drive. This next phase leverages LLMs, VLMs, and VLAs to bring unprecedented reasoning, planning capabilities, and interactivity with the driving system to autonomous vehicles and general robotics. Let’s build the future of autonomy—together! What You’ll Be Doing: • Design and train innovative large-scale models—including generative, imitation, and reinforcement learning—to improve the planning and reasoning capabilities of our driving systems. • Build, pre-train, and fine-tune LLM/VLM/VLA systems for deployment in real-world autonomous driving and robotics applications. • Explore novel data generation and collection strategies to improve diversity and quality of training datasets. • Collaborate with cross-functional teams to deploy AI models in production environments, ensuring performance, safety, and reliability standards are met. • Integrate machine learning models directly with vehicle firmware to deliver production-quality, safety-critical softw…
工作职责
N/A
• Design and implement the DSL and the core compiler of tile-aware GPU programming model for emerging GPU architectures • Continuously innovate and iterate on the core architecture of the compiler to consistently optimize performance • Investigation of next-generation GPU architectures and provide solutions in the DSL and compiler stack • Performance analysis on emerging AI/LLM workloads and integrate with AI/ML frameworks
We are looking for a Software Test development engineer in NVIDIA’s Deep Learning SWQA team. The position is in NVIDIA Deep Learning Software Quality Assurance team that defines, develops and performs tests to validate robustness and measure the performance of NVIDIA‘s Deep Learning software and GPU Infrastructure for autonomous driving, healthcare, speech recognition, natural language processing, and a wide variety of other AI scenarios. This team collaborates with multiple AI product teams to develop new products; derive and improve complex test plans; and improve our workflow processes for a diverse range of GPU computing platforms. You should grow with being in the critical path supporting developers working for billion-dollar business lines as well as intimately understanding the values of responsiveness, thoroughness and teamwork. You should constantly foster and implement efficiency improvements across your domain. Join the team which is building software which will be used by the entire world! What you’ll be doing: • Work closely with global cross-functional teams to understand the test requirements and take ownership of product quality. • Plan/design/execute/report/automate test plan/test case/test reports. • Manage bug lifecycle and co-work with inter-groups to drive for solutions. • Automate test cases and assist in the architecture, crafting and implementing of test frameworks. • In-house repro and verify customer issues/fixes. • Utilize AI-powered tools to improve efficiency and quality, including test case/plan/script generation, defect detection, CBTP, bug fixing and day to day assistance.
We are looking for a Software Test development engineer in NVIDIA’s AI SWQA team. The position is in NVIDIA AI Software Quality Assurance team that defines, develops and performs tests to validate robustness and measure the performance of NVIDIA‘s AI software and GPU Infrastructure for autonomous driving, healthcare, speech recognition, natural language processing, and a wide variety of other AI scenarios. This team collaborates with multiple AI product teams to develop new products; derive and improve complex test plans; and improve our workflow processes for a diverse range of GPU computing platforms. You should grow with being in the critical path supporting developers working for billion-dollar business lines as well as intimately understanding the values of responsiveness, thoroughness and teamwork. You should constantly foster and implement efficiency improvements across your domain. Join the team which is building software which will be used by the entire world! What you’ll be doing: • Work closely with global cross-functional teams to understand the test requirements and take ownership of product quality. • Plan/design/execute/report/automate test plan/test case/test reports. • Manage bug lifecycle and co-work with inter-groups to drive for solutions. • Automate test cases and assist in the architecture, implementing/enabling test for CI/CD. • In-house repro and verify customer issues/fixes.
We are looking for a Software Test development engineer in NVIDIA’s Deep Learning SWQA team. The position is in NVIDIA Deep Learning Software Quality Assurance team that defines, develops and performs tests to validate robustness and measure the performance of NVIDIA‘s Deep Learning software and GPU Infrastructure for autonomous driving, healthcare, speech recognition, natural language processing, and a wide variety of other AI scenarios. This team collaborates with multiple AI product teams to develop new products; derive and improve complex test plans; and improve our workflow processes for a diverse range of GPU computing platforms. You should grow with being in the critical path supporting developers working for billion-dollar business lines as well as intimately understanding the values of responsiveness, thoroughness and teamwork. You should constantly foster and implement efficiency improvements across your domain. Join the team which is building software which will be used by the entire world! What you’ll be doing: • Work closely with global cross-functional teams to understand the test requirements and take ownership of product quality. • Plan/design/execute/report/automate test plan/test case/test reports. • Manage bug lifecycle and co-work with inter-groups to drive for solutions. • Automate test cases and assist in the architecture, crafting and implementing of test frameworks. • In-house repro and verify customer issues/fixes. • Utilize AI-powered tools to improve efficiency and quality, including test case/plan/script generation, defect detection, CBTP, bug fixing and day to day assistance.