Job Description

:

• Plan, design, and iterate the machine learning platform product, covering the full process from model training, evaluation, deployment, to inference.
• Design and optimize the platform's visual UI Portal to continuously improve efficiency and experience for algorithm and business users.
• Fully understand the needs of algorithm, R&D, and other teams to form clear product plans and priority roadmaps.
• Track the internal development team's progress and launches, drive cross-department collaboration, and ensure timely version delivery.
• Collect and analyze feedback from external users (business teams) on platform usage and establish a closed-loop mechanism for issues and requirements.
• Continuously monitor trends in machine learning platforms, AI infrastructure, and generative AI, and drive platform capability upgrades.

Requirements :

• Bachelor's degree or above, preferably in Computer Science, Software Engineering, Artificial Intelligence, or related fields.
• At least 1 year of product management experience, familiar with basic processes of Internet products or AI/technical platform products.
• Basic understanding of the lifecycle of machine learning models from training, evaluation, deployment to inference.
• Strong communication and cross-team collaboration skills, able to coordinate algorithm, engineering, and business resources efficiently.
• Strong logical analysis and problem-solving abilities, capable of driving complex system productization.
• Experience with algorithm platforms, model management platforms, or online inference platforms is a plus; experience with AI-related products is preferred.

About the Team :
The EGO team is dedicated to building a leading machine learning platform that fully supports the efficient deployment of algorithms across multiple business areas, including recommendations, search, and advertising. The platform focuses on CTR/CVR prediction in large-scale sparse feature scenarios and generative recommendation combined with LLMs. It deeply optimizes the entire model training and online inference process, providing low-latency, high-throughput, and high-accuracy inference services in e-commerce, content, and social scenarios, serving as a core algorithm support and growth engine for the business.
The platform covers the full lifecycle of deep learning, including data/sample generation, feature engineering, model training, model deployment, online inference, and monitoring. We have built a complete training/inference acceleration framework with a supporting Web UI and RESTful API, aiming to achieve a truly end-to-end automated and intelligent machine learning platform.

Skills Required