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.

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'll be doing:

• Define the strategy and execution plans for successfully integrating complex AI model tech stacks in customer environments, fromevaluation/proof-of-concepttodesign/development/qualification/validation,to production launch

• Execute the plan you craft by: scoping the project, identifying and assembling the core support team, formally kicking off the project with customers, developing a joint project timeline, supporting the design-in effort by providing technical collateral/tools, leading engineering design reviews, ensuring the implementation of certain customer-required features, driving resolution of any blocking issues, and ensuring timely customer acceptance and production deployment

• Translate customer requirements into specific tasks and assign those tasks to relevant functional areas with ease. Collecting, prioritizing, tracking, and driving customer-reported issues to resolution/closure is a key focus of this role.

• Clearly and intelligently communicate issue status to the customer and internal (including executive) teams

• Work closely with engineering, product management, and sales teams to resolve technical issues, set correct expectations and keep the scope of the projects on track to successful execution

• Effectively organize and lead complex technicalengineering-to-engineeringdiscussions

• Correctly represent the urgency of issues and raise them (internally and/or externally) as appropriate

• Regularly communicate program status and key issues to management

• Develop a close working relationship with customer development teams and use creativity to find solutions to their issues

What we need to see:

• BS/MS Engineering or Computer Science (or equivalent experience)

• 8+ years in a high-tech electronics industry with a focus on program/project management

• Experience and therefore deep customer savvy born of running significant and complex software engagement programs, especially with strategic customers with large datacenter deployments

• Strong technical savvy, including software qualification and deployment on AI infrastructure in a datacenter OR Cloud

• Supreme leadership skills across broad and diverse functional teams

• Validated history of 5+ years of project/program management of software product solutions

• Strong technical background and experience working with customers in a clouddevelopment/deploymentand/or OEM environment

• Experience leading global projects

Ways to stand out from the crowd:

• Graphics, and/or cloud datacenterdevelopment/deploymentexperience desirable

• Comfortable defining and executing complex program schedules with intimate understanding of dependencies, critical paths, key and critical landmarks, and deliverables

• Consistent record of handling multiple customers and customer programs across worldwide geographies and time zones

What you will be doing:

• Develop and implement cloud security features and solutions for aspects such as cheat detections, privilege critical issues that are scalable, reliable, and secure.

• Conduct security assessments of our cloud infrastructure, services, and applications to identify potential vulnerabilities and recommend security improvements.

• Partner with peer development teams to verify that hardware deployments, datacenter configurations, services, and applications maintain security and enforce relevant security standards.

• Develop, review, and roll out security controls, such as access controls, encryption, intrusion detection, and data loss prevention.

• Develop and maintain security policies and procedures.

• Keep up to date with emerging security threats and trends; develop strategies to mitigate these risks.

• Collaborate with other security and IT teams in NVIDIA to ensure that security guidelines are coordinated into all aspects of our cloud-based infrastructure.

• Support the transfer of security knowledge and expertise to GeForce Now product team members.

What we need tosee:

• BS, os MS in Computer Science, Electrical Engineering, or Computer Engineering (or equivalent experience).

• 3+ years of proven experience.

• Proven knowledge of the Kubernetes platform, with a track record of working with and securing a global cloud environment.

• Solid understanding of cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP) or Oracle Cloud Infrastructure (OCI).

• Solid security architecture knowledge of key building blocks such as networking, data ingress/egress technologies,authentication/authorizationdesign patterns, encryption standards for data in transit and in persistence, and data integrity controls.

• Hands-on secure cloud development and deployment experience

• Understanding of security compliance frameworks such as PCI-DSS, HIPAA, and SOC2.

• Excellent problem-solving skills and the capacity to work autonomously as well as collaboratively.

• Strong communication skills, with the ability to clearly articulate technical information to both technical and non-technical audiences.

Ways to stand out from thecrowd:

• Practical experience in working on cloud IaaS platform or operating services

• Proven hands-on experience with more than one public cloud platform.

• Relevant certifications such as Certified Cloud Security Professional (CCSP), Certified Information Systems Security Professional (CISSP), or equivalent.