דרושים Deep Learning Performance Architect - New College Grad ב-אנבידיה ב-China, Beijing, Beijing

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.

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.

What you'll be doing:

• Study and develop cutting-edge techniques in CUDA programming, profiling, optimization. Application domains include deep learning, graphic, 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.

• Work directly with key customers to understand the current and future problems they are solving and provide the best AI solutions using GPUs.

• Collaborate closely with the architecture, research, libraries, tools, and system software teams at NVIDIA to influence the design of next-generation architectures, software platforms, and programming models.

What we need to see:

• A degree from university in an engineering or computer science related discipline (BS; MS or PhD preferred).

• Strong knowledge of C/C++, software design, programming techniques, GPU arch, parallel computing, and AI algorithms.

• Prefer solid skills of CUDA C/C++ programming, performance profiling and optimization.

• Prefer expert knowledge of GPU arch.

• Good communication skills.

What you'll be doing:

• Developing and implementing GPU solutions that cater to both graphics and computing workloads using NVIDIA’s innovative technology.

• Engaging directly with customers to understand their requirements and provide flawless solutions, ensuring their success with NVIDIA products.

• Working closely with internal teams to identify and effectively implement GPU solutions that align with our rigorous quality standards.

• Applying your expertise with NVIDIA GPUs, including CUDA, frameworks, and SDKs, to achieve world-class performance and reliability.

• Leading and participating in customer projects, encouraging a collaborative and inclusive environment to achieve shared objectives.

What we need to see:

• A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent program.

• 5+ years of experience.

• Demonstrated background working with NVIDIA GPU technology, encompassing Graphics, CUDA, frameworks, and SDKs.

• Proficient knowledge in handling graphics and computational tasks on NVIDIA GPUs.

• Outstanding communication prowess, adept at expressing thoughts in English verbally and in writing.

• Demonstrated ability to work effectively in a team setting, contributing to project success.

• Experience interacting with customers while comprehending and attending to their requirements.

• Familiarity with infrastructure skills such as Kubernetes (k8s) and a deep understanding of public cloud techniques is a plus.

What you'll be doing:

• Primary responsibilities will include building AI/HPC infrastructure for new and existing customers.

• Support operational and reliability aspects of large-scale AI clusters, focusing on performance at scale, real-time monitoring, logging, and alerting.

• Engage in and improve the whole lifecycle of services—from inception and design through deployment, operation, and refinement.

• Maintain services once they are live by measuring and monitoring availability, latency, and overall system health.

• Provide feedback to internal teams such as opening bugs, documenting workarounds, and suggesting improvements.

What we need to see:

• BS/MS/PhD or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering fields with at least 8 years work or research experience in networking fundamentals, TCP/IP stack, and data center architecture.

• 8+ years of experience with configuring, testing, validating, and issue resolution of LAN and InfiniBand networking, including use of validation tools for InfiniBand health and performance including medium to large scale HPC/AI network environments.

• Knowledge and experience with Linux system administration/dev ops, process management, package management, task scheduling, kernel management, boot procedures, troubleshooting, performancereporting/optimization/logging,andnetwork-routing/advancednetworking (tuning and monitoring).

• Driven focus on customer needs and satisfaction. Self-motivated with excellent leadership skills including working with customers.

• Extensive knowledge of automation, delivering fully automated network provisioning solutions using Ansible, Salt, and Python.

• Strong written, verbal, and listening skills in English are essential.

Ways to stand out from the crowd:

• Linux or Networking Certifications.

• Experience with High-performance computing architectures. Understanding of how job schedulers(Slurm, PBS) work.

• Proven knowledge of Python or Bash. Infrastructure Specialist's delivery experience

• Luster management technologies knowledge (bonus credit for BCM (Base Command Manager).)

• Experience with GPU (Graphics Processing Unit) focused hardware/software as well as experience with MPI (Message Passing Interface.)

What You’ll Be Doing:

• Design and train innovative large-scale models—including generative, imitation, and reinforcement learning—to enhance 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 software.

What We Need to See:

• 5+ years of experience in developing software infrastructure for large scale AI systems.

• Bachelor's degree or higher in Computer Science or a related technical field (or equivalent experience).

• Hands-on experience building LLMs, VLMs, or VLAs from scratch or a proven track record as a top-tier coder passionate about autonomous systems.

• Deep understanding of modern deep learning architectures and optimization techniques.

• Proven record of deploying production-grade ML models for self-driving, robotics, or related fields at scale.

• Strong programming skills in Python and proficiency with major deep learning frameworks.

• Familiarity with C++ for model deployment and integration in safety-critical systems.

Ways to Stand Out from the Crowd:

• Experience with LLM/VLM/VLA systems deployable to autonomous vehicles or general robotics. Or publications, open-source contributions, or competition wins related to this field.

• Deep understanding of behavior and motion planning in real-world AV applications.

• Experience building and training large-scale datasets and models.

• Proven ability to optimize algorithms for real-time performance in resource-constrained environments.

• Strong track record of taking projects from concept to production deployment.