Solutions Architect - Financial Service Retail jobs at Nvidia in China, 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'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.)

focused Solution Architect with expertise inLarge Language Model, generative AI, or recommender system. We work with the most exciting computing hardware and software, driving the latest breakthroughs in artificial intelligence. We need individuals who can enable customer productivity and develop lasting relationships with our technology partners, making NVIDIA an integral part of end-user solutions. We are looking for someone always thinking about artificial intelligence, someone who can maintain constructive collaboration in a fast paced, rapidly evolving field, someone able to coordinate efforts between corporate marketing, industry business development and engineering. You will be working with the latest AI architecture coupled with the most advanced neural network models, changing the way people interact with technology.

As a Solutions Architect, you will be the first line of technical expertise between NVIDIA and our customers. Your duties will vary from working on proof-of-concept demonstrations, to driving relationships with key executives and managers to evangelize accelerated computing. Dynamically engaging with developers, scientific researchers, data scientists, IT managers and senior leaders is a meaningful part of the Solutions Architect role and will give you experience with a range of partners and concerns.

What you’ll be doing:

• Assisting field business development in guiding the customer build/extend their GPU infrastructures for AI.

• Help customers build their large-scale projects, especially Large Language Model (LLM) projects.

• Engage with customers to perform in-depth analysis and optimization to ensure the best performance on GPU architecture systems. This includes support in optimization of both training and inference pipelines.

• Partner with Engineering, Product and Sales teams to develop, plan best suitable solutions for customers. Enable development and growth of product features through customer feedback and proof-of-concept evaluations.

• Build industry expertise and become a contributor in integrating NVIDIA technology into Enterprise Computing architectures.

What we need to see:

• MS or PhD in Electrical Engineering, Computer Science/Engineering, Mathematics, Physics, or a related field (or equivalent experience).

• 3+ years of work-related experience in AI for natural language processing (NLP) and large language model (LLM).

• Knowledge of application areas such as natural language processing and computer vision.

• Excellent programming skills in some rapid prototyping environments such as Python, C++ and parallel programming (e.g., CUDA) is a plus.

• Expertise with deep learning frameworks such as PyTorch.

• Strong written and oral communications skills in English.

Ways to stand out from the crowd:

• Background in large language model, generative AI, recommender system.

• Demonstrated experience optimization workloads with GPU technology.

• Experience with NVIDIA AI and Data Science software and platform.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us. If you are creative and autonomous, we want to hear from you!

NVIDIA is committed to encouraging a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What you’ll be doing:

• Apply your experience and knowledge in areas of accelerated computing and machine learning (esp. AI4S, Robotic, Life science, LLM, VLM, VLA, GAI and agentic AI).

• Conduct AI engineering via playing with software and hardware and collaborating with external researchers. Partner with internal groups to transfer technologies and innovate products.

• Deliver NVIDIA tools and software to researchers and developers. Present value of NVIDIA total solution to customers.

• Assist in building AIGC, AI4S tools with the state-of-the-art AI models. It can also help the AI community use multiple NVIDIA SDKs or frameworks (esp.PhysicsNeMo/Modulus/CUDA-Q/Isaac/BioNeMo)to realize fantastic ideas!

What we need to see:

• Masters/Ph.D in Computer Science, Electrical Engineering, or a related field. 5 years above working experience.

• Programming experience and proficiency in CUDA, Python, C/C++, and familiar with Linux developing environment.

• Deep understanding of accelerated computing, AI for science, Robotics, Simulation Technology, Agentic AI, physical AI and LLM ecosystem

• Extensive knowledge and experience with recent advancements in AI for Science, LLMs, VLMs, VLA, Agentic AI and Physical AI.

• Ability to communicate effectively in a collaborative environment.

• Passionate about AI and its evolving growth with continuous learning spirit, self-started and driven on focused outcome oriented activities

Ways to stand out from the crowd:

• Experience and/or theoretical knowledge in accelerated computing, Robotics, AI for life science, VLA, GAI, Physical AI, etc

• Knowledge in Isaac Sim/Lab, Omniverse for digital twins, AI models training and inference for protein structure, medical imaging, gene computing,transformer/diffusionmodel, understanding the optimization methods, and having published relevant papers.

• Skills in CUDA, Robotics and deep learning frameworks (i.e TensorFlow or PyTorch).

What you'll be doing:

• Analyze state-of-the-art DL networks (LLM etc.), identify and prototype performance opportunities to influence SW and Architecture team for NVIDIA's current and next gen inference products.

• Develop analytical models for the state-of-the-art deep learning networks and algorithm to innovate processor and system architectures design for performance and efficiency.

• Specify hardware/software configurations and metrics to analyze performance, power, and accuracy in existing and future uniprocessor and multiprocessor configurations.

• Collaborate across the company to guide the direction of next-gen deep learning HW/SW by working with architecture, software, and product teams.

What we need to see:

• BS, MS or PhD in relevant discipline (CS, EE, Math, etc.) or equivalent experience.

• 5+ years’ work experience.

• Experience with popular AI models (e.g., LLM and AIGC models)

• Be familiar with typical deep learning SW framework (e.g.,Torch/JAX/TensorFlow/TensorRT)

• Knowledge and experience on hardware architectures for deep learning applications

Ways to stand out from the crowd:

• Background with CUDA and GPU computing systems

• Experience on performance modelling or optimization of DL workloads