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 to drive operational improvements • Strong interpersonal skills, effective communication skills and the ability to influence and communicate across all levels of the organization Preferred Qualifications • Management experience in a global organization • Experience scaling operations in a fast-paced and dynamic environment • Excellent verbal and written communication skills • Good analytical skills to use data to optimize the organizational efficiency and drive strategic decision making • Bachelor’s degree above or equivalent experience
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
About TI As a global semiconductor company, we design, manufacture, test and sell analog and embedded processing chips to nearly 100,000 customers. Our products enable electronics everywhere and in things you experience every day - from health care, smart homes and connected cars to drones, smart phones and more. Our passion to create a better and more sustainable world by making electronics more affordable through semiconductors drives us to make our technology smaller, more efficient, more reliable and more affordable. About the Job The AI Engineer will drive implementation of artificial intelligence and machine learning solutions to enhance semiconductor back-end manufacturing operations. The role will involve close collaboration with manufacturing teams, data scientists, product and process engineers to identify opportunities and implement AI-driven solutions that improve operational efficiency, quality, and yield. This position requires a strong understanding of AI/ML technologies, experience with semiconductor manufacturing, and a passion for applying data-driven techniques to solve complex industrial problems. Responsibilities include: • Collaborate with cross-functional teams and domain experts to identify opportunities for AI integration in workflows. • Analyze and preprocess large datasets from manufacturing equipment, sensors, and logs to enable effective machine learning applications. • Lead proof-of-concept projects and pilot programs to demonstrate the value of AI applications in manufacturing settings. • Develop and deploy AI/ML models for defect detection, yield improvement, process optimization, and predictive maintenance in semiconductor back-end manufacturing processes. • Provide technical documentation, training, and support to ensure seamless adoption of AI solutions by production teams. • Monitor AI systems performance and implement enhancement. Stay updated with the latest advancements in AI/ML and propose innovative solutions applicable to semiconductor manufacturing.
The Senior Solutions Architect (SA) role is a pre-sales technical position in Alibaba Cloud’s international business division. Our seasoned solution architects offer comprehensive IT knowledge and industry insights when crafting solutions for customers and partners. Solution Architects are ultimately responsible for architect solutions that enable customer success. Key responsibilities include, but are not limited to: • Working closely with customers to ensure the successful delivery of Alibaba Cloud services • Design large-scale, compliant cloud infrastructures (e.g., multi-cloud, edge computing) for AI workloads (LLMs, computer vision, MLOps). • Guiding large enterprise implementation and operation, preferably in AIML/GenAI projects. • As a cloud solution architect, evangelizing and helping customers and partners understand the technical and business benefits of Alibaba Cloud products, solutions, and services • Understanding the unique requirements of customers and partners, and providing appropriate technical solutions and architecture designs based on Alibaba Cloud technologies, solutions, and services • Responsible for demo development and testing Alibaba Cloud services when necessary • Assisting customers in migrating their existing IT systems to Alibaba Cloud • Output a market insight analysis report of segmented fields based on demand information such as market development trends, market space, core scenarios, and pain points in the segmented fields. • Produce targeted solutions according to customer needs, in the project, develop a correct product selection strategy, POC test strike strategy, bidding & bid strategies, product configuration strategy, etc., achieve contract signing, and continuously ensure the increase of Alibaba Cloud's market share with this customer. • Promote the incubation and replication of public cloud solutions in segmented fields. • Identify and deal with risks of the technology and project during the solution landing process on time, collaborate with the product and delivery teams for normal fulfillment, and achieve revenue conversion. • Accumulate knowledge documentation such as universal cloud architecture templates, best practices, and cases for the segmented fields/scenarios. • Provide presentations, evangelism, and empowerment training for sales teams and eco-partners. • Abstract and summarize product requirements and defects in segmented fields, promote product improvement, new product projects, and major functions launch, and enhance product competitiveness.