Quantitative Ux Researcher Google Cloud 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:

• 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:

• Enhance and maintain current-generation infrastructure and tools, addressing the needs of our customers for better platform capabilities, performance, and stability.

• Support partners in the development and deployment of their streaming experiences.

• Deploy various services and oversee their reliability and security.

• Write effective, clear and reliable architecture requirements and design specifications.

• Work closely and simultaneously with multiple NVIDIA expert teams around the world.

What we need to see:

• B.Sc./M.Sc. degree in Computer Science, Computer Engineering (or equivalent experience).

• 10+ years experience as a Full-Stack Software Developer.

• Broad knowledge and understanding of networking protocols and common network topologies, with a deep understanding of Cloud-based audio and video streaming.

• Hands-on cloud virtualization, networking, and orchestration experience.

• A combination of React, Javascript, Typescript, C/C++, Python or Go programming skills.

• Willingness to be full-stack across both frontend and backend is a must.

• Ability to understand customer needs and translate them into functional and user experience enhancements.

• Hands-on Linux development experience.

• Strong design, coding, analytical, debugging, and problem-solving skills.

• Excellent communication, documentation, and presentation skills.

Ways to stand out from a crowd:

• Background with data center technologies, network topologies and Cloud.

• Experience with Docker, Containers, Kubernetes components & subsystems.

• Experience with Proton and other virtualization technologies.

• Good understanding of operating systems and drivers.

• Experience developing and deploying deep-learning models: LLMs, text-to-speech, and more.

What you’ll be doing:

• Design, build, and run cloud infrastructure services in scope to meet our business goals performing integrations, migrations, bringups, updates, and decommissions as necessary.

• Participate in the definition of our internal facing service level objectives and error budgets as part of our overall observability strategy.

• Eliminate toil or automate it where the ROI of building and maintaining automation is worth it.

• Practice sustainable blameless incident prevention and incident response while being a member of an on-call rotation.

• Consult with and provide consultation for peer teams on systems design best practices.

• Participate in a supportive culture of values-driven introspection, communication, and self-organization

What we need to see:

• Proficiency in one or more of the following programming languages: Python or Go

• BS degree in Computer Science or a related technical field involving coding (e.g., physics or mathematics) or equivalent experience.

• 5+ years of relevant experience in infrastructure and fleet management engineering.

• Experience with infrastructure automation and distributed systems design developing tools for running large scale private or public cloud systems at scales requiring fully automated management and under active customer consumption in production.

• A track record demonstrating a mix of initiating your own projects, convincing others to collaborate with you, and collaborating well on projects initiated by others.

• In-depth knowledge in one or more of the following: Linux, Slurm, Kubernetes, Local and Distributed Storage, and Systems Networking.

Ways to stand out from the crowd:

• Demonstrating a systematic problem-solving approach, coupled with clear communication skills and a willingness to take ownership and get results such as experience driving a build / reuse / buy decision.

• Experience working with or developing bare metal as a service (BMaaS) associated systems. For example, vending BMaaS, or Slurm running on containers, or vending Kubernetes clusters. Experience working with or developing multi-cloud infrastructure services. Experience teaching reliability engineering (e.g. SRE) and/or other scale-oriented cloud systems practices to peers and/or other companies (e.g. CRE). Experience in running private or public cloud systems based on one or more of Kubernetes, OpenStack, Docker or Slurm.

• Experience with accelerated compute and communications technologies such BlueField Networking, Infiniband topologies, NVMesh, and/or the NVIDIA Collective Communication Library (NCCL).

• Experience working with a centralized security organization to prioritize and mitigate security risks. Prior experience in a ML/AI focused role or on a team matching specific keywords is welcome but not required.