苹果Principle Regulatory Affairs Associate

THE ROLE: AMD is looking for a strategic software engineering lead to drive next-generation AI inference systems, intelligent model routing, and cloud-native deployment technologies for AMD Instinct GPUs. In this role, you will work at the intersection of LLM serving, semantic routing, Kubernetes, Envoy, AI gateways, and open-source infrastructure. You will be a member of a core team of talented industry specialists focused on enabling high-performance, production-ready AI software on the latest AMD hardware and ROCm software stack. This role is especially focused on advancing intelligent routing and system-level optimization for LLM inference, including vLLM, vLLM Semantic Router, multi-model serving, policy-driven routing, semantic caching, observability, privacy-aware routing, and workload-aware optimization across AMD GPU platforms. THE PERSON: The ideal candidate is a hands-on technical leader with deep expertise in cloud-native infrastructure, open-source development, and AI inference systems. The candidate should be passionate about building scalable systems from 0 to 1, driving open-source communities, and solving complex performance, reliability, and deployment challenges. The candidate should be comfortable working across engineering, architecture, product, partner, and open-source communities. Strong communication, technical writing, public speaking, and community leadership skills are essential. The successful candidate will be able to translate emerging AI infrastructure trends into practical software solutions that strengthen AMD’s position in the open-source AI ecosystem. KEY RESPONSIBILITIES: Lead the design and development of intelligent routing technologies for LLM serving on AMD Instinct GPUs, including semantic routing, workload-aware routing, policy-based routing, and multi-model inference orchestration.Drive AMD enablement and optimization for vLLM Semantic Router and related open-source AI gateway technologies, ensuring strong support for ROCm and AMD GPU platforms.Collaborate with AMD architecture, ROCm, kernel, compiler, and AI framework teams to identify and optimize bottlenecks in LLM inference workloads.Develop production-quality software components for AI inference systems, including routers, gateways, control-plane services, observability tools, policy engines, and deployment automation.Build and optimize integrations across vLLM, Kubernetes, Envoy, Gateway API, service mesh, and AI gateway ecosystems.Apply a data-driven approach to performance analysis, including benchmarking, profiling, latency analysis, throughput optimization, and cost-efficiency evaluation.Contribute to open-source communities and represent AMD in key AI infrastructure projects, including vLLM, Kubernetes, Envoy, Gateway API, and related CNCF ecosystems.Develop technical relationships with external partners, customers, researchers, and community maintainers to accelerate AMD adoption in AI inference workloads.Create technical documentation, blogs, demos, reference architectures, and conference presentations to showcase AMD’s AI software capabilities.Participate in new AMD GPU platform bring-up activities by validating AI inference software stacks, debugging system-level issues, and developing early proof points for emerging workloads.Research and prototype new approaches for system intelligence in LLM serving, including semantic caching, prompt classification, privacy-aware routing, safety-aware routing, tool routing, agent routing, and workload-router-pool architectures.PREFERRED EXPERIENCE: Strong software engineering background with experience building distributed systems, cloud-native infrastructure, AI infrastructure, or high-performance serving systems.Deep experience with Kubernetes, Envoy, Gateway API, service mesh, ingress/gateway controllers, or cloud-native networking.Experience contributing to or maintaining major open-source projects, preferably in CNCF, Kubernetes, Envoy, Istio, vLLM, or AI infrastructure communities.Experience with LLM serving frameworks such as vLLM, SGLang, TensorRT-LLM, or related inference-serving systems.Experience with semantic routing, AI gateways, model routing, policy-based routing, semantic caching, prompt classification, or multi-model inference orchestration.Strong programming skills in Go, Rust, Python, and/or C/C++. Go and Rust experience are especially valuable for cloud-native control planes, gateways, and high-performance routing systems.Experience with Linux systems, containerized deployments, distributed debugging, observability, and production reliability.Familiarity with GPU-accelerated AI workloads, ROCm, CUDA, ONNX Runtime, PyTorch, or inference performance optimization is a strong plus.Experience with performance profiling, benchmarking, latency optimization, memory optimization, and high-concurrency serving systems.Ability to write high-quality, maintainable code with strong attention to architecture, reliability, testing, and operational simplicity.Strong technical communication skills, including technical writing, public speaking, community engagement, and cross-functional collaboration.Demonstrated ability to lead complex technical projects from concept to production and influence without direct authority across organizations and open-source communities.Motivating technical leader with excellent interpersonal skills and the ability to work effectively in global, distributed teams.ACADEMIC CREDENTIALS: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, or equivalent experience.Advanced degree or research experience in AI systems, distributed systems, cloud-native infrastructure, machine learning systems, or high-performance computing is a plus.#LI-JW2

Description - External Co-work with and thus support software development teams Leads software product architecture design, involves in product detailed design and review, covers the whole software life cycle, based on Schneider Electric product platforms and market requirements to enhance edge systems portfolio Act as key developer and owner of highly reusable and exceptionally reliable fundamental software components Work with project teams to provide software consultations to customers and other stakeholders

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.

- Own the go-to-market playbook for ad products in China — from launch planning to driving sustained advertiser adoption and revenue. - Build sales strategies that work — create positioning, competitive battle cards, and sales plays that help the field team win deals faster. - Be the voice of the market — gather frontline feedback from advertisers and sales teams, then turn it into clear recommendations that influence the product roadmap. - Lead cross-team execution — coordinate across Product, Sales, Marketing, and Services to ensure nothing falls through the cracks at launch. - Track what matters — define adoption KPIs, build dashboards, and lead business reviews with leadership using data-driven insights. - Shape the long-term vision — author strategic planning docs (3-year vision, PR/FAQs) that align leadership on where we're going and why. - Enable sales at scale — train field teams on new capabilities and partner with Marketing on localized messaging for Chinese advertisers.