苹果AIML - Data Operations Senior Team Lead (Shanghai)
任职要求
Minimum Qualifications • Minimum 8 to 10 years experience in people management, leading teams focused on consumer-facing applications, content or service • Ability to empower and drive the team’s performance and be accountable for business priorities • Self-starter with forward thinking capability, strategic vision, and strong executional track record • Experience defining and analyzing KPI’s, with the ability to identify trends and opportunities for innovation and improvement • Proven track record of collaborating cross-functionally t…
工作职责
In this role, you will be leading day-to-day operations to ensure organizational delivery of high quality annotated data from the group of Team Leads you support. You will effectively lead team performance by developing Team Leads, and other Senior Annotation roles, through individual coaching, team meetings, mentor sessions, participating in interviewing and hiring, data analysis, and collaboration with other Data Operations sites. You’ll also assist in the development of tools and reports needed analyze and run the business, including workflow optimization, workforce management, and developing more efficient ways of working. You will help determine staffing requirements and participate in interviewing and hiring. The role is an office based position. Additionally, some specific supervisor shifts require certain hours to be present on campus, and can span any hours of operations.
Product Strategy & Development • Lead the development of AI-driven product strategies to drive NBS AI penetration • Identify growth opportunities across seller segments and lifecycle stages • Design and implement AI solutions that enhance seller success metrics and operational efficiency • Drive efficiency and productivity of seller recruitment, account management or go-to-market activities • Lead continuous product optimization based on user feedback Technical Leadership • Partner with data science and engineering teams to develop and implement AI/ML solutions • Define clear technical requirements and success metrics for AI-powered features • Oversee development cycles and ensure successful deployment of solutions • Drive data-informed decision making across product initiatives Stakeholder Management • Lead cross-functional collaboration between central product and program management teams, technical teams, business stakeholders, and external partners • Drive effective communication of product strategy, roadmap, and impact analysis to leadership • Manage change initiatives and stakeholder alignment across CN team and MP teams
Product Strategy & Development • Lead the development of AI-driven product strategies to drive NBS AI penetration • Identify growth opportunities across seller segments and lifecycle stages • Design and implement AI solutions that enhance seller success metrics and operational efficiency • Drive efficiency and productivity of seller recruitment, account management or go-to-market activities • Lead continuous product optimization based on user feedback Technical Leadership • Partner with data science and engineering teams to develop and implement AI/ML solutions • Define clear technical requirements and success metrics for AI-powered features • Oversee development cycles and ensure successful deployment of solutions • Drive data-informed decision making across product initiatives Stakeholder Management • Lead cross-functional collaboration between central product and program management teams, technical teams, business stakeholders, and external partners • Drive effective communication of product strategy, roadmap, and impact analysis to leadership • Manage change initiatives and stakeholder alignment across CN team and MP teams
Product Strategy & Development • Lead the development of AI-driven product strategies to drive NBS AI penetration • Identify growth opportunities across seller segments and lifecycle stages • Design and implement AI solutions that enhance seller success metrics and operational efficiency • Drive efficiency and productivity of seller recruitment, account management or go-to-market activities • Lead continuous product optimization based on user feedback Technical Leadership • Partner with data science and engineering teams to develop and implement AI/ML solutions • Define clear technical requirements and success metrics for AI-powered features • Oversee development cycles and ensure successful deployment of solutions • Drive data-informed decision making across product initiatives Stakeholder Management • Lead cross-functional collaboration between central product and program management teams, technical teams, business stakeholders, and external partners • Drive effective communication of product strategy, roadmap, and impact analysis to leadership • Manage change initiatives and stakeholder alignment across CN team and MP teams
• Capture business requirements, translate requirements into functional design, user stories, technical design, drive end to end integration testing, support data set up and issue remediation during UAT, manage development team activities, develop hypercare support model • Define and architect AI agents for Supply Chain use cases, using the right frameworks, multi-agent coordination, RAG, deployment, monitoring, and life cycle management. • Be hands on in quick proof of concepts development to demonstrate technical feasibility and implement enterprise grade Agentic Supply Chain solutions • Partner with Enterprise IT engineering, product, and research teams while evaluating LLMs, agentic frameworks, and NVIDIA’s own NeMo technologies. • Ensure integration with enterprise IT and Operations data sources and Industry’s best Agentic platforms with strong content security focus. • Drive architectural decisions across deployment models (on-prem, cloud, hybrid, containerized) to deliver scalable, reliable, and efficient solutions. • Lead design reviews, develop technical documentation, and guide developers in principles of architecture and code development. • Champion observability, monitoring, versioning, and telemetry to ensure trustworthy and auditable AI agents. • Influence Supply Chain Operations adoption of the platform by partnering with stakeholders across IT, supply chain and serve as a reference adopter providing feedback to strengthen NVIDIA’s ecosystem.