苹果AI Application Engineer
任职要求
Minimum Qualifications • - Bachelor's degree in Computer Science, Engineering, or related field with a minimum of 5+ years of relevant industry experience in AI application development, machine learning, or software engineering • - Strong understanding of generative AI models(e.g. LLMs such as GPT, BERT) and their application in real-world solutions, such as chatbots, NLP applications, and content generation • - Excellent software engineering skills, with expertise in modular, object-oriented design, and familiarity with industry-standard development processes. Proficiency in Python, PHP, Java, Git preferred. • - Comfort with ambiguity, with the ability to structure complex analysis and drive insights through data exploration and strategy research. Preferred Qualifications • - 3+ years of hands-on experience developing multi-agent systems or agent-based modeling, with experience in frameworks like MAS platforms, NetLogo, or AnyLogic • - Proven experience in multi-agent coordination platforms (MCP) or related frameworks • - Hands-on experience with cloud platforms, such as AWS, Azure, GCP, with expertise in deploying and managing scalable AI Platform. • - Extensive knowledge and hands-on experience with popular LLMs, such as Gemini, Claude, and GPT, including the ability to fine-tune and optimize these models for specific use cases. • - Solid understanding of popular AI/ML frameworks(e.g. TensorFlow, PyTorch, scikit-learn) and experience with MCP tools for multi-agent coordination and AI system integration • - Curious, self-motivated, and able to drive improvements to model evaluation pipelines and annotation programs. • - Eagerness and ability to learn new skills and solve dynamic problems in an encouraging and expansive environment. • - Outstanding communication skills – both written and verbal – with experience presenting to leadership.
工作职责
• In this role, you will • - AI Solution Development: Design, develop, and deploy AI-driven applications, across domains, such as machine learning, NLP, and computer vision, addressing both business requirements and end-user needs. • - Agent Design and Development: Design and implement intelligent agents within multi-agent systems, enabling real-time collaboration based on pre-defined goals, strategies, and data exchanges. Develop agent-based models to optimize decision-making and interactions. • - MCP Integration: Extend and integrate Multi-Agent Coordination Platforms(MCP) to optimize resource allocation, communication, and decision-making across multiple agents in shared environments. • - Collaboration with Data Science Teams: Collaborate with data scientists to refine algorithms, optimize models, and enhance AI performance, focusing on model tuning, feature selection, and performance benchmarking • - Testing and Validation: Conduct rigorous testing and validation of AI models, including unit testing, integration testing, and A/B testing, to ensure accuracy, reliability, and scalability before deployment. • - Monitoring and Maintenance: Monitor deployed AI models, track performance metrics, and implement continuous improvement strategies, including model re-training and updates based on real-world data and evolving business needs.
We are seeking a skilled developer to build production-grade AI applications, focusing on LLM-based agents and tool-using systems. You will integrate large language models (LLMs), retrieval-augmented generation (RAG), and external tools/APIs on GPU-accelerated stacks, enhancing agent frameworks for reliability, scalability, and safety. What You’ll Be Doing: • Design, implement, and deploy AI-powered features using LLMs, including autonomous and multi-agent workflows. • Build agent toolchains, including planning, tool/function calling, memory management, RAG integration, and enterprise API connectivity. • Enhance agent frameworks with custom planners, routers, concurrency control, state management, and retry mechanisms. • Develop evaluation and observability systems to monitor agent performance (success rates, tool-call accuracy, latency, cost, traces). • Implement safety and compliance measures, including content filtering, PII handling, and policy enforcement using guardrail frameworks. • Optimize inference pipelines for GPU performance, latency, and cost; deploy via microservices and APIs. • Manage CI/CD, containerization, and deployment; maintain monitoring, logging, and alerting; and produce clear documentation.
THE ROLE: Join AMD China Datacenter GPU Platform Application Engineering team as an Application Engineering Director, leading a high-performing group of engineers supporting Data Center GPU customers in the Greater China market. In this customer-facing role, you will collaborate with external MDC, OEM/ODM and CSP partners, AI end users, internal development and validation teams, and many other cross-functional stakeholders to bring next-generation AI server platforms to market powered by AMD’s Instinct™ Accelerators, ensure the successful deployment in customer data centers, and support customer workloads performance turning, optimization and successful production. THE PERSON: Description of what type of person would be successful in the role and any characteristics needed. (typically soft skills). KEY RESPONSIBILITIES: Team Leadership: Manage a team of Application Engineers engaged in validating AMD GPU products within China customers’ AI server platforms, supporting OEM/ODM factory operations, enabling customer datacenter deployments. Working with other geo leadership and other China leadership, strategize DC GPU China technical leadership growth and development, and continue to grow and build a highly performant PAE team in China. Issue Resolution: Oversee the triage, debugging, and resolution of customer issues, ensuring timely coordination with internal engineering and product teams, and drive issue closure. Escalation Management: Serve as the primary escalation point for complex customer engineering challenges, driving resolution and customer satisfaction. Technical Guidance: Collaborate with OEM/ODM partners closely on AMD tools enablement and validation methodologies, driving China customer co-validation strategy. Manufacturing Enablement: Collaborate with OEM/ODM factory teams to develop manufacturing scripts and test programs that ensure reliability at scale. Datacenter Enablement & Deployment: Support MDC/CSP customer datacenter deployment and technical issue resolution. Customer Communication: Drive the team to create and review technical information disclosure, training materials, and other customer-facing documentation. Resource & Onboarding Management: Direct hardware resources allocation, continue to manage, develop and grow a high-performing PAE team in China. Strategic Representation: Lead and drive strategic planning and cross-functional initiatives.
THE ROLE: Join the AMD AECG (Adaptive and Embedded Computing Group) as the leader of our China Customer Engineering team to further strengthen and grow the team. In this role, you will lead the customer program engagements and deep customer co-engineering supporting Embedded x86 customers in the Greater China market. In this customer-facing role, you will collaborate with local FAE and sales managers, global Customer Applications Engineering teams and R&D Engineering teams, and many other cross-functional stakeholders to ensure successful, on-time and high-quality deployment of AMD Embedded x86 processors into customer designs from evaluation through development and production. You will also build strong and deep relationships with engineering leaders of the customers and be the influential voice of customer internally. Key market segments are networking, storage, automotive and edge-AI. THE PERSON: Brief description of what type of person would be successful in the role and key traits needed KEY RESPONSIBILITIES: Team Leadership: Lead a team of local Customer Application Engineers and other technical experts who may be remote to engage with China customers to adopt and develop designs with AMD Embedded x86 processors. Build and grow the Greater China Customer Engineering team through hiring and team development. Evaluations and Design-Wins: Engage yourself and team deeply with customers to understand the key care-abouts, enable hands-on evaluations and build compelling technical and architectural engagement to win China customer designs working closely with global teams Issue Resolution / Customizations: Oversee the triage, debugging, and resolution of customer issues, ensuring timely coordination with internal engineering and product teams, and drive issue closure. Build strongly technical team to create and deliver custom features in self-contained fashion. Escalation and Crises Management: Serve as the primary escalation point for complex customer engineering challenges, driving resolution and customer satisfaction. Technical Guidance: Provide training and support to customers and ODMs to adopt AMD Embedded x86 processors, development tools and design guides. Customer Communication: Drive the team to create and review technical information disclosure, training materials, and other customer-facing documentation. Resource & Onboarding Management: Direct hardware resources allocation, continue to manage, develop and grow a high-performing Customer Engineering team in China. Build strong competent team with the key expertise needed for emerging markets. Deep Partnership and Co-engineering with Customers : Built a customer obsessed team of strong technical engineers who can work in deep co-engineering working model with customers and this partnership building a competitive moat.
• Co-work with the architect to define module architecture/micro-architecture. • Building for NVIDIA next next-generation IPs • Involved in the entire ASIC flow.