产品数据运营项目经理

Manage and deliver product data operations programs that support AI model training, evaluation, and deployment pipelines across multiple product teams

Partner with research, engineering, and product teams to define data requirements, align on quality standards, and prioritize data collection and annotation efforts for AI solutions

Identify and resolve bottlenecks in data labeling, annotation, and curation workflows to ensure timely delivery of high-quality training datasets

Break down complex data operations challenges into manageable components, applying systematic analysis to design and implement scalable solutions aligned with AI product roadmaps

Develop and maintain program documentation including data governance frameworks, workflow specifications, risk registers, and milestone tracking for AI data initiatives

Engage team leaders and cross-functional stakeholders to build alignment on program direction, surface risks proactively, and drive decisions that unblock data operations work

Track and communicate program health metrics — including data throughput, quality rates, and delivery timelines — adapting communication style and format to technical and non-technical audiences

Leverage AI tools and workflow automation to improve the efficiency and quality of data operations processes, sharing learnings to scale adoption across the team

Contribute to team-level goal setting by synthesizing insights from data operations performance and translating them into actionable recommendations for AI product teams

Adapt program plans in response to shifting AI product priorities, regulatory requirements, or data availability constraints, maintaining focus on highest-impact deliverables

6+ years of experience in program management, data operations, or technical operations roles supporting AI, machine learning, or data-driven product development;

or 2+ years of such experience with a Bachelor's degree in Computer Science, Artificial Intelligence, Computer Engineering, Human-Computer Interaction, or a related technical field

Fundamental understanding of AI/ML model development and the data requirements across the model lifecycle — including training, evaluation, and fine-tuning data needs

Experience managing cross-functional programs involving data pipelines, data labeling, annotation workflows, or AI training data quality initiatives

Experience in analyzing operational data and communicating findings and recommendations to technical and non-technical stakeholders at varying levels of leadership

Experience identifying process inefficiencies and implementing scalable solutions within data or AI operations environments

Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

Experience using AI-powered tools or workflow automation platforms to redesign and accelerate data operations processes, including demonstrated application of responsible and ethical AI practices such as bias mitigation and quality review

Master's degree in Computer Science, Artificial Intelligence, Computer Engineering, Human-Computer Interaction, or a related technical field

Experience working directly with research or machine learning teams to define data requirements and evaluate the quality of datasets for AI model development

Familiarity with data governance practices, metadata management, or compliance considerations relevant to AI training data

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or 2+ years of such experience with a Bachelor's degree in Computer Science, Artificial Intelligence, Computer Eng