安克创新Deep Learning Engineer Specialist

- As an AIML Specialist Solutions Architect (SA) in AI Infrastructure, you will serve as the Subject Matter Expert (SME) for providing optimal solutions in model training and inference workloads that leverage Amazon Web Services accelerator computing services. As part of the Specialist Solutions Architecture team, you will work closely with other Specialist SAs to enable large-scale customer model workloads and drive the adoption of AWS EC2, EKS, ECS, SageMaker and other computing platform for GenAI practice. - You will interact with other SAs in the field, providing guidance on their customer engagements, and you will develop white papers, blogs, reference implementations, and presentations to enable customers and partners to fully leverage AI Infrastructure on Amazon Web Services. You will also create field enablement materials for the broader SA population, to help them understand how to integrate Amazon Web Services GenAI solutions into customer architectures. - You must have deep technical experience working with technologies related to Large Language Model (LLM), Stable Diffusion and many other SOTA model architectures, from model designing, fine-tuning, distributed training to inference acceleration. A strong developing machine learning background is preferred, in addition to experience building application and architecture design. You will be familiar with the ecosystem of Nvidia and related technical options, and will leverage this knowledge to help Amazon Web Services customers in their selection process. - Candidates must have great communication skills and be very technical and hands-on, with the ability to impress Amazon Web Services customers at any level, from ML engineers to executives. Previous experience with Amazon Web Services is desired but not required, provided you have experience building large scale solutions. You will get the opportunity to work directly with senior engineers at customers, partners and Amazon Web Services service teams, influencing their roadmaps and driving innovations.

Are you someone who thrives in a in a fast-paced organization? We are currently seeking a Senior Account Manager! NVIDIA is experiencing rapidly growing demand for L2–L4 autonomous driving solutions in China. We are looking for a Senior Account Manager to cover key automotive OEM clients. You will collaborate with cross-functional teams to deliver NVIDIA’s cutting-edge technologies and solutions to our customers. What you’ll be doing: • Drive NVIDIA revenue in large auto accounts • Engage with various NVIDIA technology partners and identify areas of collaboration. Identify complementary technologies needed to build complex solutions using our computing platforms. • Create go-to-market execution w/ cross functional teams • Prioritize and report on key business metrics to measure and guide global industry teams. • Influence and align with sales and customer teams to understand customer requirements and build a scale out plan for target market technologies • Generating technology trends and market analysis • Represent and evangelize NVIDIA solutions at key industry events

• Hold and articulate the vision for Trust & Safety at Supercell: Ensure that safety, fairness, and player well-being remain at the core of our social experiences. Hold and articulate the vision for Trust & Safety at Supercell • Lead: Foster a culture where senior subject matter experts, developers, and operators thrive, and help the team align around shared goals that will have the greatest impact for our players. Lead • Drive operational excellence: Ensure smooth day-to-day functioning of Trust & Safety across the program, data, operations, and development sub-cells. Drive operational excellence: • Drive strategic alignment: Lead the development of clear, ambitious, and achievable objectives for the team, and create space for the team to define the best paths toward achieving them. Drive strategic alignment • Champion the smart use of technology and AI: Help the team explore, evaluate, and implement new technical approaches to improve detection, prevention, and player experience. Champion the smart use of technology and AI • Be a partner and connector: Work closely with Player Care, “Heads Of” games, and other partners across Supercell to ensure we support the most social experiences in a way that cares for the safety of our players. Be a partner and connector • Be a confident and calming presence: The work is challenging and sometimes emotionally charged, the Lead must be a stabilizing presence at all times. Be a confident and calming presence: • Elevate external awareness and internal alignment: Highlight emerging risks, newsworthy events, and strategic recommendations to internal stakeholders, while also contributing to industry discussions on best practices. Elevate external awareness and internal alignment • Invest in growth and learning: Coach and support team members to broaden their expertise in safety, wellness, regulation, technology, and research, helping them stay ahead of evolving challenges. Invest in growth and learning • Measure and improve: Oversee reporting on effectiveness, quality, and impact, and ensure insights from data and operations inform continuous improvement. Measure and improve • Remove barriers: Surface and resolve roadblocks that prevent the team from doing their best work, and advocate for the resources and support they need. Remove barriers

Position Overview We are seeking a highly experienced engineer specializing in large language model (LLM) inference performance optimization. You will be a core member of our team, responsible for building and optimizing the LLM inference performance with high-throughput, low-latency on AMD Instinct GPUs. If you are passionate about pushing performance boundaries and have deep, hands-on expertise with cutting-edge technologies like vLLM or SGLang, we invite you to join us. Key Responsibilities 1. Core System Optimization: Lead the development, tuning, and customization of LLM performance optimization on AMD GPUs, leveraging and extending frameworks like vLLM or SGLang to address performance bottlenecks in production environments. 2. Performance Analysis & Tuning: Conduct end-to-end performance profiling using specialized tools. Perform deep optimization of compute-bound operators (e.g., Attention), memory I/O, and communication to significantly increase throughput and reduce latency. 3. Model Architecture Adaptation: Demonstrate expertise in mainstream LLM architectures (e.g., DeepSeek, Qwen, Llama, ChatGLM) and optimize inference for their specific characteristics (e.g., RoPE, SWA, MoE, GQA). 4. Algorithm & Principle Application: Leverage your deep understanding of core algorithms (Transformer, Attention, MoE) to implement advanced optimization techniques such as PagedAttention, FlashAttention, continuous batching, quantization, and model compression. 5. Technology Foresight & Implementation: Research and prototype state-of-the-art optimization techniques (e.g., Speculative Decoding, Weight-Only Quantization) and drive their adoption into production systems. Qualifications: Mandatory