Llm Reinforcement Learning Algorithm Engineer - New College Grad jobs at Nvidia in China, Shanghai

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

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.

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.

• 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

What you will be doing:

• Design and implementfunctional/performancetests for CUDA products, like driver and library.

• Automate CUDA tests, design test plans and integrate into automation testinginfrastructure.

• Triage test results, root cause test failures or performance drops, and drive through bugs to fix.

• Develop scripts/tools and optimize workflow to improve efficiency and productivity.

What we need to see:

• MS or PhD degree from a leading university in computer science or a related field.

• At least 3 years of relevant professional experience.

• Excellent QA sense, knowledge, and experience in software testing.

• Rich experience in test case development, tests automation and failure analysis.

• Proficient programming and debugging skills in C/C++ and Python.

• Comprehensive knowledge of Linux and Windows operating systems.

• Experience in using AI development tools for test plans creation, test cases development and test cases automation.

Ways to stand out from the crowd:

• Excellent English communication and collaboration skills.

• Strong understanding of CUDA, HPC, Gcov, VectorCAST, Coverity.

What you'll be doing:

• Use internally developed tools and industry standard pre-silicon gate-level and RTL power analysis tools, to help improve product power efficiency.

• Develop and share best practices for performing pre-silicon power analysis, Enhance internal power tools and automate best practices

• Perform comparative power analysis, to spot trends and anomalies, that warrant more scrutiny.

• Interact with architects and RTL designers to help them interpret their power data and identify power bugs; drive them to implement fixes.

• Select and run a wide variety of workloads for power analysis, Collaborate with performance and architecture teams to validate performance of the workloads

• Prototype a new architectural feature in Verilog and analyze power.

What we need to see:

• EE, MS or PhD in related fields, or equivalent experience.

• Basic understanding of concepts of energy consumption, estimation, and low power design.

• Familiarity with Verilog and ASIC design principles, including knowledge of logic cells.

• Good verbal/written English and interpersonal skills; much collaboration with design teams is expected.

• Strong coding skills, preferably in Python, C++.

• Ability to formulate and analyze algorithms, and comment on their time complexity and memory consumption.

• Desire to bring data-driven decision-making and analytics to improve our products.

Ways to stand out from the crowd:

• Familiar with the power tools/flow development is a big plus

What you'll be doing:

• Work on NVIDIA's next generation of Video Decoder and Encoder hardware architecture.

• Research and study new video compression technology, specifications, papers etc.

• Develop c-model for algorithm study, hardware simulation and verification.

• Define the testplan, write architecture document, verify c-model and improve model coverage.

What we need to see:

• Master degree or above in Computer Science, Electronic Engineering.

• Minimum of 3 years' experience in the field of video technology ranging from codec, implementation, pre/post-processing, rate control and etc.

• Good programming skill and C/C++ coding abilities.

• Fluent English (both written and spoken) and good communication skill.

Ways to stand out from the crowd:

• Project experiences in video encoder, decoder or computer vision.

• Experience with video codec such as H264,HEVC, VP9, AV1or VVC.

• Experience with DL video/image processing.

• Creative, strong analysis, design and debug skill.