System Architect jobs

What you’ll be doing:

• Working with tech giants to develop and demonstrate solutions based on NVIDIA’s groundbreaking software and hardware technologies.

• Partnering with Sales Account Managers and Developer Relations Managers to identify and secure business opportunities for NVIDIA products and solutions.

• Serving as the main technical point of contact for customers engaged in the development of intricate AI infrastructure, while also offering support in understanding performance aspects related to tasks like large scale LLM training and inference.

• Conducting regular technical customer meetings for project/product details, feature discussions, introductions to new technologies, performance advice, and debugging sessions.

• Collaborating with customers to build Proof of Concepts (PoCs) for solutions to address critical business needs and support cloud service integration for NVIDIA technology on hyperscalers.

• Analyzing and developing solutions for customer performance issues for both AI and systems performance.

What we need to see:

• BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience.

• 4+ years of engineering(performance/system/solution)experience.

• Hands-on experience building performance benchmarks for data center systems, including large scale AI training and inference.

• Understanding of systems architecture including AI accelerators and networking as it relates to the performance of an overall application.

• Effective engineering program management with the capability of balancing multiple tasks.

• Ability to communicate ideas clearly through documents, presentations, and in external customer-facing environments.

Ways to stand out from the crowd:

• Hands-on experience with Deep Learning frameworks (PyTorch, JAX, etc.), compilers (Triton, XLA, etc.), and NVIDIA libraries (TRTLLM, TensorRT, Nemo, NCCL, RAPIDS, etc.).

• Familiarity with deep learning architectures and the latest LLM developments.

• Background with NVIDIA hardware and software, performance tuning, and error diagnostics.

• Hands-on experience with GPU systems in general including but not limited to performance testing, performance tuning, and benchmarking.

• Experience deploying solutions in cloud environments including AWS, GCP, Azure, or OCI as well as knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes, data center deployments, etc. Command line proficiency.

What you’ll be doing:

• Work closely with passionate engineers to design, develop, optimize, debug, unit test, document and maintain next-generation graphics and computing features for NVIDIA GPUs.

• We work on next-generation GPU hardware and software features through all phases of development, and you will get an opportunity to work across user and kernel stacks.

• Also work on customer issues and provide timely root cause of the problem and resolution.

• Collaborate with many internal teams (software, hardware, architecture, QA and OEM support), partners and customers to define new products and features, and resolve issues.

What we need to see:

• BS degree or higher or equivalent experience (computer science or related).

• 12+ years of industry experience.

• In depth understanding of Windows or Linux device drivers, PC architecture and ability to work close to the hardware.

• Proficient in C/C++ with strong software development, optimization and analytical skills.

• Strong debugging skills and extensive experience using gdb/kgdb/windbg to analyze complex pieces of software.

• Strong articulation skills for crafting and improving technical documents, and to engage globally distributed engineering team.

Ways to stand out from the crowd:

• Understanding of Virtualization concepts and system software for ESX, Hyper-V or KVM.

• Knowledge of DX/OGL graphics technologies, WDDM model.

• Familiarity with computer system architecture, microprocessor, and microcontroller fundamentals (caches, buses, memory controllers, DMA, etc.).

What You'll Be Doing:

• Working as a key member of our cloud solutions team, you will be the go-to technical expert on NVIDIA's products, helping our clients architect and optimize GPU solutions for AI services.

• Collaborating directly with engineering teams to secure design wins, address challenges, usher projects into production, and offer support through the project's lifecycle.

• Acting as a trusted advisor to our clients, while developing reference architectures and best practices for running Microsoft AI workloads on NVIDIA infrastructure.

What We Need To See:

• 4+ years of experience in cloud computing and/or large-scale AI systems.

• A BS in EE, CS, Math, or Physics, or equivalent experience.

• A proven understanding of cloud computing and large-scale computing systems.

• Proficiency in Python, C, or C++ and experience with AI frameworks like Pytorch or TensorFlow.

• Passion for machine learning and AI, and the drive to continually learn and apply new technologies.

• Excellent interpersonal skills, including the ability to explain complex technical topics to non-experts.

Ways To Stand Out From The Crowd:

• Recent projects or contributions (for example, on GitHub) related to large language models and transformer architectures.

• Knowledge of Azure cloud and AzureML services.

• Experience with CUDA programming and optimization.

• Familiarity with NVIDIA networking technologies such as Infiniband.

• Proficiency in Linux, Windows Subsystem for Linux, and Windows.

What you’ll be doing:

• 100% kernel coding role

• Own end-to-end design and development, challenging existing paradigms and exploring innovative approaches for RDMA and high-speed TCP-based networks.

• Collaborate closely with cross-functional teams to define and implement robust networking algorithms, data management strategies, and distributed systems principles.

• Contribute to architecture, integration, and alignment with both on-prem and cloud-native platforms.

• Optimize system performance and reliability through in-depth analysis and low-level tuning.

• Stay up to date with the latest industry trends and contribute to open-source projects.

What we need to see:

• B.S. or M.S. degree in Computer Science or Electrical Engineering (or equivalent experience).

• 12+ years experience in development

• Proven professional experience in designing and developing distributed systems; advantage for experience in block storage and networking systems, advantage for cloud environments.

• Strong proficiency in C/C++ programming. Experienced with Linux Kernel internals including block subsystem, IO stack, memory management, and scheduling.

• Familiarity with storage protocols and standards, especially NVMe.

• Knowledge of networking fundamentals and experience in Linux-based networking environments.

• Familiarity with RDMA technologies, including Infiniband, RoCE, or iWARP, and experience with RDMA programming models, control and data paths.

• Knowledge of cloud computing concepts, including virtualization, scalability, and data management.

Ways To Stand Out From The Crowd:

• Excellent communication skills and a collaborative mindset.

• Perseverance and determination in debugging complex problems.

What you will be doing:

You will be responsible for design, development, and delivery of core components of our next-generation VLSI productivity platforms.

• Design, build, deploy, and improve highly scalable systems

• Translate high-level requirements into actionable plans/deliverables

• Leverage LLMs to accelerate (not replace) your contribution while taking ownership of your output

• Convert legacy codebases into modern powerhouses infused with industry best-practices

• Collaborate with engineering teams to identify and alleviate bottlenecks in their daily tasks

What we need to see:

• B.S. CS/EE (or equivalent experience)

• 5+ years developing large-scale software applications in Go and Python

• Solid computer science fundamentals in algorithms/datastructures/complexityanalyses

• Understand processes, synchronization, locks, concurrency, and load-balancing

• Excellent grasp of distributed systems and compute abstractions

• Experience building custom solutions around open-source products and libraries to solve feature-gaps fast

Ways to stand out from the crowd:

• 5+ years in an enterprise engineering environment, shipping at scale

• Experience in partitioning and optimizing complex interconnected systems

• Understand filesystems, job-scheduling, and inter-process signaling

• Highly self-sufficient in the face of ambiguity, with strong reasoning and problem-solving skills

• Rapid comprehension of existing codebases (in any language) to implement high-leverage changes effectively

What you will be doing:

You will be responsible for design, development, and delivery of core components of our next-generation VLSI productivity platforms.

• Design, build, deploy, and improve highly scalable systems

• Translate high-level requirements into actionable plans/deliverables

• Leverage LLMs to accelerate (not replace) your contribution while taking ownership of your output

• Convert legacy codebases into modern powerhouses infused with industry best-practices

• Collaborate with engineering teams to identify and alleviate bottlenecks in their daily tasks

What we need to see:

• B.S. CS/EE (or equivalent experience)

• 5+ years developing large-scale software applications in Go and Python

• Solid computer science fundamentals in algorithms/datastructures/complexityanalyses

• Understand processes, synchronization, locks, concurrency, and load-balancing

• Excellent grasp of distributed systems and compute abstractions

• Experience building custom solutions around open-source products and libraries to solve feature-gaps fast

Ways to stand out from the crowd:

• 5+ years in an enterprise engineering environment, shipping at scale

• Experience in partitioning and optimizing complex interconnected systems

• Understand filesystems, job-scheduling, and inter-process signaling

• Highly self-sufficient in the face of ambiguity, with strong reasoning and problem-solving skills

• Rapid comprehension of existing codebases (in any language) to implement high-leverage changes effectively