该职位来源于猎聘
Job Posting/Job Ad SUMMARY This role focuses on designing, developing, and deploying machine learning and generative AI models that transform Kids2's enterprise data into intelligent business solutions. The engineer will build AI agents such as copilots, chatbots, and workflow assistants that integrate with existing systems like SAP S4/HANA, Workday, SharePoint, Workfront, Smartsheet, and Salsify to enhance decision-making and automation across the organization. Key responsibilities include developing semantic models and data layers for natural language querying, partnering with data engineering teams on scalable database architectures, and translating business challenges into measurable AI-powered use cases. The role requires ongoing model monitoring, lifecycle management, and API integration with enterprise systems. The position involves extensive collaboration with global teams in English, participating in meetings and documentation while executing AI projects defined by the company's AI task force. The ultimate goal is to support Kids2's AI-first strategy by unlocking the value of enterprise data through intelligent, automated solutions. PRIMARY RESPONSIBILITIES AND ESSENTIAL FUNCTIONS: Design and develop machine learning models using enterprise data from ERP, HRIS, document management, project management, and product information management systems Deploy generative AI models and solutions into production environments Implement model monitoring, performance tracking, and retraining processes Manage AI model lifecycle from development through retirement Build conversational AI agents (copilots, chatbots, workflow assistants) for business users Create automated workflows that integrate AI capabilities with existing business processes Develop natural language interfaces for querying enterprise data and systems Design and maintain semantic models and data layers for AI applications Integrate AI solutions with enterprise systems through APIs and orchestration frameworks Partner with data engineering teams on scalable, secure database architectures Ensure data quality, governance, and privacy compliance across AI initiatives Translate business challenges into measurable AI-powered use cases and solutions Execute AI projects defined by the company's AI task force Analyze and optimize AI solution performance to drive business impact Collaborate with global stakeholders in English through meetings, documentation, and project updates QUALIFICATIONS & EXPERIENCE
Years of Experience: Minimum 3+ years in AI/ML engineering roles with hands-on experience building and deploying AI agents 2+ years working with enterprise data integration and database architecture Experience with ERP, HRIS, MES, document management, or project management systems Type of Experience Required: Industry Background: Manufacturing, technology, consulting, or other data-intensive industries Experience with global enterprise environments and complex system integrations Background working with large-scale business operations and cross-functional teams Role Experience: AI/ML Engineer, Data Scientist, or Software Engineer with AI focus Enterprise system integration specialist or business intelligence developer Technical roles involving API development and system orchestration Experience translating business requirements into technical AI solutions Technical Experience: Hands-on development with Python, SQL, and ML frameworks Building intelligent agents, chatbots, or conversational AI interfaces Database architecture design and semantic model development API integration and enterprise system connectivity AI model lifecycle management and performance monitoring EDUCATION & SKILLS
Education: Level Required: Bachelor's degree minimum; Master's degree preferred 3-5 years of relevant education in technical fields Career Fields: Computer Science or Software Engineering Data Science or Data Engineering Artificial Intelligence or Machine Learning Information Systems or Management Information Systems Engineering disciplines (Industrial, Systems, etc.) Mathematics, Statistics, or Applied Analytics Skillset and Competencies: Technical Skills: Programming proficiency in Python and SQL Machine learning frameworks Database architecture and semantic model design API development and system integration Enterprise data platform experience (cloud or on-premise) Version control, CI/CD, and software development best practices AI/ML Competencies: Model development, training, and deployment Natural language processing and conversational AI Data preprocessing and feature engineering Model performance monitoring and optimization AI governance and explainability principles Business Competencies: Enterprise system understanding (ERP, HRIS, project management tools) Business process analysis and requirements gathering Cross-functional collaboration and stakeholder management Problem-solving and analytical thinking Project management and delivery execution Additional Languages: English: Conversational proficiency required for global team collaboration, meetings, and technical documentation Mandarin Chinese: Native or fluent (for local operations in Zhongshan) CERTIFICATES, LICENSES, REGISTRATIONS While certifications are preferred, equivalent hands-on experience and demonstrated competency may substitute for formal credentials. COMPUTER/TECHNICAL SKILLS
This role requires strong programming skills in Python and SQL, along with proficiency in machine learning frameworks and AI model development. Candidates must have experience with database architecture design, API development, and enterprise system integration. Knowledge of cloud platforms (AWS, Azure, Google Cloud) and modern data platforms like Snowflake or Databricks is highly valued. Experience with MLOps tools for model lifecycle management and version control systems is essential. Understanding of enterprise systems architecture and integration patterns for ERP, HRIS, and project management platforms completes the technical requirements.