甲骨文Principal Cloud Solution Engineer

Responsibilities Collaborate with GPU sales team and SCE AIML TPM team to provide technical support for customers both at pre-sales and after-sales stage. Take ownership of problems and work to identify solutions. Design, deploy, and manage infrastructure components such as cloud resources, distributed computing systems, and data storage solutions to support AI/ML workflows. Collaborate with customers’ scientists and software/infrastructure engineers to understand infrastructure requirements for training, testing, and deploying machine learning models. Implement automation solutions for provisioning, configuring, and monitoring AI/ML infrastructure to streamline operations and enhance productivity. Optimize infrastructure performance by tuning parameters, optimizing resource utilization, and implementing caching and data pre-processing techniques. Troubleshoot infrastructure performance, scalability, and reliability issues and implement solutions to mitigate risks and minimize downtime. Stay updated on emerging technologies and best practices in AI/ML infrastructure and evaluate their potential impact on our systems and workflows. Document infrastructure designs, configurations, and procedures to facilitate knowledge sharing and ensure maintainability. Qualifications: Experience in scripting and automation using tools like Ansible, Terraform, and/or Kubernetes. Experience with containerization technologies (e.g., Docker, Kubernetes) and orchestration tools for managing distributed systems. Solid understanding of networking concepts, security principles, and best practices. Excellent problem-solving skills, with the ability to troubleshoot complex issues and drive resolution in a fast-paced environment. Strong communication and collaboration skills, with the ability to work effectively in cross-functional teams and convey technical concepts to non-technical stakeholders. Strong documentation skills with experience documenting infrastructure designs, configurations, procedures, and troubleshooting steps to facilitate knowledge sharing, ensure maintainability, and enhance team collaboration. Strong Linux skills with hands-on experience in Oracle Linux/RHEL/CentOS, Ubuntu, and Debian distributions, including system administration, package management, shell scripting, and performance optimization.

TCS(Tencent Cloud-native Suite) is a Cloud-Native Platform for Enterprise Cloud-Native Transformation supports on-premise bare metal or third-party IaaS deployments. Product Solutions Architect (PDSA) is a key pre-sales technical position in Tencent Cloud - TCS product team. Our PDSAs are experienced solution architects with professional knowledge and industry insight and are, ultimately, the pivotal role in supporting the global sales team by providing cloud-native solutions, striving to meet product sales targets, and leading key projects for customer onboarding. Job Responsibilities: ● Acting as a subject matter expert on Tencent Cloud - TCS products (container, microservice, message queue), providing training and enablement to the account and Solution Architect (SA) teams. ● Supporting regional events and marketing programs to promote Tencent TCS solutions to potential customers. ● Delivering optimized solutions and advocating best practices to customers by utilizing the full capabilities of Tencent TCS products. ● Gathering and analyzing customer feedback to enhance product offerings, improve market competitiveness and help build the product roadmap continually. ● Monitoring key industry trends and technological shifts, offering trusted advice to customers for optimizing their IT infrastructure and improving their user experience. ● Expanding the product ecosystem through collaboration with global channels, industrial partners and third-party Independent Software Vendors (ISVs). Creating position papers, and aligning advocacy efforts with Tencent Cloud’s core business policies across multiple departments (business, security, legal, and government affairs). ● Reporting to the Head of the product architect team, this role requires a dynamic, curious, and technology-driven candidate who thrives in challenging environments and can navigate ambiguity with strategic insight.

The Role Tesla is looking for a technical and industry-experienced engineer to join a team of talented engineers. As part of Tesla IT Operation team, we are responsible to deliver 7x24 system infrastructure and provides a portfolio of services including configuration management, engineering tools, identity access and control, managing public, private cloud infrastructure, ensure security and extreme reliability is our fundamental design principal, the candidate must be hands-on on day-to-day basis with experience in building, operating and driving reliability and security for production systems at scale. Responsibilities • Responsible for the design, deployment, and support of manufacturing systems and network infrastructure. • Provide support for China-based infrastructure build-out, including datacenter, Linux system (both virtualized and bare-metal servers). • Installation, configuration, and maintenance of Linux server environment. • Ensure the reliability of the existing systems to guarantee uptime and availability of core infrastructure services. • Perform root-cause analysis of complex issues ranging through hardware, operating system, application, network, and information security platforms. • work with different business units to identify, plan, test and deploy or upgrade Linux system according to business requirements. • Partner with teams from across the organization to help tackle hard problems in a collaborative, high velocity environment. • Tackle issues across the entire stack: hardware, software, network and application. • Managing engineering tools and platform such as GitHub, Artifactory, etc. • Perform analysis, troubleshooting, and introspection on core infrastructure components and handle incident response. • Creating and maintain well documented knowledge base and be a mentor of junior engineers. • Take on call role and respond quickly to emergency bridge and provide quick and effective solutions to minimize system downtime.

• Design, build, and optimize containerized inference execution for LLM applications, ensuring efficiency and scalability. These applications may run in container orchestration platforms like Kubernetes to enable scalable and robust deployment. • Ensure the performance and scalability of NIMs through comprehensive performance measurement and optimization. • Apply container expertise to create and optimize the basic building blocks of NIMs, influencing the development of many models and related products within NVIDIA. • Collaborate, brainstorm, and improve the designs of inference solutions and APIs with a broad team of software engineers, researchers, SREs, and product management. • Mentor and collaborate with team members and other teams to foster growth and development. Demonstrate a history of learning and enhancing both personal skills and those of colleagues.