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What You’ll Be Doing:
Conduct in-depth analysis of customers' latest needs and co-develop accelerated computing solutions with key customers.
Assist in supporting industry accounts and drivingresearch/influencing/newbusiness in those accounts.
Deliver technical projects, demos and client support tasks as directed by the Solution Architecture leadership team.
Understand and analyze customers' workloads and demands for accelerated computing, including but not limited to: LLM training/inference acceleration and optimization, application optimization for Agent AI/RAG, kernel analysis, etc.
Assist customers in onboarding NVIDIA's software and hardware products and solutions, including but not limited to: CUDA, TensorRT-LLM,NeMoFramework, etc.
Be an industry thought leader on integrating NVIDIA technology into applications built on Deep Learning, High Performance Data Analytics, Robotics, Signal Processing and other key applications.
Be an internal champion for Data Analytics, Machine Learning, and Cyber among the NVIDIA technical community.
What We Need To See:
3+ years’ experience withresearch/development/applicationof Machine Learning, data analytics, or computer vision work flows.
Outstanding verbal and written communication skills
Ability to work independently with minimal day-to-day direction
Knowledge of industry application hotspots and trends in AI and large models.
Familiarity with large model-related technology stacks and common inference/training optimization methods.C/C++/Python programming experience
Desire to be involved in multiple diverse and innovative projects
Experience using scale-out cloud and/or HPC architectures for parallel programming
MS or PhD in Engineering, Mathematics, Physics, Computer Science, Data Science, Neuroscience, Experimental Psychology or equivalent experience.
Ways To Stand Out From The Crowd:
AIGC/LLM/NLP experience
CUDA optimization experience.
Experience with Deep Learning frameworks and tools.
Engineering experience in areas such as model acceleration and kernel optimization.
Extensive experience designing and deploying large scale HPC and enterprise computing systems.
These jobs might be a good fit

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What you will be doing:
Investigate and resolve sensor calibration and egomotion algorithm/toolchain issues across multiple OEM vehicle platforms.
Develop core autonomous driving functionality for global markets by fusing state-of-the-art perception DNNs with map signals.
Build real-time 3D world models for planning, integrating diverse inputs from sensors and external sources.
Develop and optimize LLM, VLM, and VLA systems for autonomous driving applications, including pre-training and fine-tuning.
Design innovative data generation and collection strategies to improve dataset diversity and quality.
Collaborate with cross-functional teams to deploy end-to-end AI models in production, ensuring performance, safety, and reliability standards are met.
What we need to see:
A MS, or PhD, or equivalent professional experience in Computer Science, Computer Engineering, Mathematics, Physics, or a related discipline.
Over 3 years of relevant industry experience.
Expertise in C/C++ programming, with a comprehensive understanding of standard C++ features, algorithms, and data structures, along with proficiency in Linux environments.
In-depth knowledge of parameter models for sensor calibration.
A solid grasp of digital image processing, three-dimensional multi-view geometry, nonlinear optimization, and KF/EKF.
A robust mathematical foundation, especially in matrix-related concepts.
Engineering expertise in developing and delivering deep learning applications for autonomous vehicles or robotics
Engineering expertise in developing and delivering real-time 3D world models for planning in AV system.
Excellent collaboration skills and the ability to work effectively with individuals from various nationalities and locations.
Ways to stand out from the crowd:
Experience with a range of sensors and their data (camera, lidar, radar, IMU, GNSS, CAN Odometry).
Extensive experience in SLAM algorithms
Extensive deep learning experience related to autonomous driving.
A track record of designing SLAM algorithms for successful ADAS projects.

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What you will be doing:
You will work and develop state of the art techniques in deep learning, graphs, machine learning, and data analytics, and perform in-depth analysis and optimization to ensure the best possible performance on current- and next-generation GPU architectures
You will provide the best AI solutions using GPUs working directly with key customers
Collaborate closely with the architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and programming models
What we need to see:
Pursuing MS or PhD from a leading University in an engineering or Computer Science related discipline
Strong knowledge of C/C++, software design, programming techniques, and AI algorithms
Experience with parallel programming, ideally CUDA C/C++
Good communication and organization skills, with a logical approach to problem solving, time management, and task prioritization skills
Preferred internship duration: 4+ months

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What you’ll be doing:
Be responsible for running test cases to validate NVIDIA GPU Communications Libraries (NCCL, NVSHMEM, UCX, GDRCopy, GPUDirect RDMA etc).
Be responsible to automate test cases and maintain the automation scripts.
Collaborate with Developer, PM, marketing, and engineering teams on crafting test plan and implementing validation.
You will assist in the architecture, crafting and implementing of SWQA test frameworks.
Be responsible for code coverage improvement and code complexity optimization.
What we need to see:
BS or higher degree in CS/EE/CE or equivalent experience
5+ years of relevant experience
Seasoned software QA or software testing background; test infrastructure and strong analysis skills
Be proficient in scripting language (Python, Perl, bash)
Solid experience with AI development tools for test development and automation
Knowledge of basic networking concepts
UNIX/Linux experience is required
Experiences in C/C++ is required
Ability to work independently and leadership skillsas well as experience in using quality mindset to drive improvements
Proficient oral and written English
Ways to stand out from the crowd:
Experience with CUDA programming and NVIDIA GPUs
Knowledge of high-performance networks like InfiniBand, RoCE,etc
Experience with CSPs(AWS, Google Cloud, Oracle Cloud Infrastructure, Microsoft Azure), andHPC cluster,slurm, ansible, etc
Prior experience with virtualization technologies (KVM, HyperV, VMWARE, OpenStack, Docker, Kubernetes)
Experience with Deep Learning Frameworks such as PyTorch, TensorFlow, etc

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What you’ll be doing:
Work with architects and performance architects to develop an energy-efficient GPU.
Develop methodologies and workflows to select and run a wide variety of workloads to train models using ML and/or statistical techniques.
Develop methodologies to improve the accuracy of energy models under various constraints, such as, process, timing, floorplan and layout.
Correlate the predicted energy from models created at different stages of the design cycle, with the goal of bridging early estimates to silicon.
Develop tools to debug energy inefficiencies observed in various workloads run on silicon, RTL and architectural simulators. Work with architects to fix the identified energy inefficiencies.
Work with performance, verification and emulation methodology and infrastructure development teams to integrate energy models into their platforms.
Prototype new architectural features, create an energy model, and analyze the system impact.
What we need to see:
MS degree with 1 year experience in related fields or equivalent experience
Strong coding skills, preferably in Python, C++.
Background in machine learning, AI, and/or statistical modeling.
Interest in computer architecture and energy-efficient GPU designs.
Familiarity with Verilog and ASIC design principles is a plus.
Ability to formulate and analyze algorithms, and comment on their runtime and memory complexities.
Desire to bring quantitative decision-making and analytics to improve the energy efficiency of our products.
Good verbal/written English and interpersonal skills.

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NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 25 years, driven by exceptional technology and outstanding individuals. Today, we're tapping into the unlimited potential of AI to define the next era of computing, where our GPU acts as the brains of immersive digital worlds and creative applications. As an NVIDIAN, you'll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work.
What you'll be doingEstablish and scale NVIDIA's neural graphics organization in China, building research and engineering teams
Define and implement our neural graphics strategy for China and its integration into NVIDIA's graphics platform
Build strategic partnerships with China's leading VLM and neural graphics research institutions and talent
Lead recruitment of exceptional talent in neural rendering, vision-language models, and differentiable programming
Drive research-to-product pipeline, translating China's VLM innovations into shipping products and platforms globally
Architect system-level integration of neural graphics technologies across NVIDIA's platform ecosystem
Represent NVIDIA across the world's graphics and AI research community, establishing thought leadership
Partner with executive leadership to develop company-wide neural graphics strategy and roadmap
Degree in Computer Science, Computer Graphics, Machine Learning, or equivalent experience that is outstanding
12+ years experience, 6+ years leading teams
Deep connections in the neural graphics research community
Proven track record of building organizations and scale teams in fast paced technical domains
Strong understanding of ML frameworks, VLM architectures, and AI technologies with experience bringing them to production
Experience defining platform strategies with demonstrated research-to-product transfers and measurable business impact across global markets
Excellent interpersonal and communication skills to lead across research, product, and executive teams in both Chinese and English
Established thought leadership in neural graphics, VLMs, or AI-powered rendering with industry recognition
Experience building successful research-industry partnerships in China's AI ecosystem
Track record shipping graphics or AI platforms used by developers worldwide
Conference presentations, publications, or awards in graphics, VLMs, or AI
Experience establishing new technical organizations or regional presences

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NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people.
What you'll be doing: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
Masters or PhD or equivalent experience in relevant discipline (CE, CS&E, CS, AI)
4 + years of relevant work experience
Excellent C/C++ programming and software engineering skills, ACM background is a plus
Good fundamental knowledges on computer architecture
Strong ability in abstracting problems and the methodology in resolving problems
Strong compiler backgrounds including MLIR/TVM/Triton/LLVM is desired
Good knowledge of GPU architecture and fast kernel programming skills is a plus
Knowledge of LLM algorithms or a certain HPC domain is a plus
Knowledge of multi-GPU distributed communication is a plus
Excellent oral communication in English is a plus

Share
What You’ll Be Doing:
Conduct in-depth analysis of customers' latest needs and co-develop accelerated computing solutions with key customers.
Assist in supporting industry accounts and drivingresearch/influencing/newbusiness in those accounts.
Deliver technical projects, demos and client support tasks as directed by the Solution Architecture leadership team.
Understand and analyze customers' workloads and demands for accelerated computing, including but not limited to: LLM training/inference acceleration and optimization, application optimization for Agent AI/RAG, kernel analysis, etc.
Assist customers in onboarding NVIDIA's software and hardware products and solutions, including but not limited to: CUDA, TensorRT-LLM,NeMoFramework, etc.
Be an industry thought leader on integrating NVIDIA technology into applications built on Deep Learning, High Performance Data Analytics, Robotics, Signal Processing and other key applications.
Be an internal champion for Data Analytics, Machine Learning, and Cyber among the NVIDIA technical community.
What We Need To See:
3+ years’ experience withresearch/development/applicationof Machine Learning, data analytics, or computer vision work flows.
Outstanding verbal and written communication skills
Ability to work independently with minimal day-to-day direction
Knowledge of industry application hotspots and trends in AI and large models.
Familiarity with large model-related technology stacks and common inference/training optimization methods.C/C++/Python programming experience
Desire to be involved in multiple diverse and innovative projects
Experience using scale-out cloud and/or HPC architectures for parallel programming
MS or PhD in Engineering, Mathematics, Physics, Computer Science, Data Science, Neuroscience, Experimental Psychology or equivalent experience.
Ways To Stand Out From The Crowd:
AIGC/LLM/NLP experience
CUDA optimization experience.
Experience with Deep Learning frameworks and tools.
Engineering experience in areas such as model acceleration and kernel optimization.
Extensive experience designing and deploying large scale HPC and enterprise computing systems.
These jobs might be a good fit